Overview

Dataset statistics

Number of variables78
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory609.5 KiB
Average record size in memory624.1 B

Variable types

Categorical29
Numeric6
Text43

Alerts

H has constant value ""Constant
1 is highly overall correlated with 1High correlation
9.10 is highly overall correlated with 9.2043 and 3 other fieldsHigh correlation
1 is highly overall correlated with 1High correlation
9.2043 is highly overall correlated with 9.10 and 3 other fieldsHigh correlation
0.0020 is highly overall correlated with 9.10 and 6 other fieldsHigh correlation
0.66 is highly overall correlated with 0.03High correlation
is highly overall correlated with .2 and 12 other fieldsHigh correlation
.1 is highly overall correlated with and 2 other fieldsHigh correlation
H.1 is highly overall correlated with High correlation
.2 is highly overall correlated with and 10 other fieldsHigh correlation
0 is highly overall correlated with 1High correlation
.3 is highly overall correlated with and 11 other fieldsHigh correlation
T is highly overall correlated with 0.03 and 1 other fieldsHigh correlation
0.03 is highly overall correlated with 0.0020 and 3 other fieldsHigh correlation
L is highly overall correlated with THigh correlation
.4 is highly overall correlated with and 12 other fieldsHigh correlation
.5 is highly overall correlated with and 11 other fieldsHigh correlation
is highly overall correlated with 0.0020 and 4 other fieldsHigh correlation
.6 is highly overall correlated with .1 and 3 other fieldsHigh correlation
.7 is highly overall correlated with .1 and 3 other fieldsHigh correlation
.8 is highly overall correlated with 0.0020 and 4 other fieldsHigh correlation
.9 is highly overall correlated with and 8 other fieldsHigh correlation
is highly overall correlated with and 12 other fieldsHigh correlation
1 is highly overall correlated with 0.0020 and 13 other fieldsHigh correlation
.10 is highly overall correlated with and 6 other fieldsHigh correlation
.11 is highly overall correlated with 0.0020 and 5 other fieldsHigh correlation
.12 is highly overall correlated with and 9 other fieldsHigh correlation
.1 is highly overall correlated with and 11 other fieldsHigh correlation
is highly overall correlated with and 9 other fieldsHigh correlation
is highly overall correlated with and 10 other fieldsHigh correlation
S is highly overall correlated with 9.10 and 1 other fieldsHigh correlation
.13 is highly overall correlated with 9.10 and 1 other fieldsHigh correlation
.14 is highly overall correlated with .12High correlation
is highly imbalanced (70.1%)Imbalance
.1 is highly imbalanced (70.6%)Imbalance
H.1 is highly imbalanced (51.0%)Imbalance
.2 is highly imbalanced (72.7%)Imbalance
0 is highly imbalanced (58.2%)Imbalance
.3 is highly imbalanced (68.4%)Imbalance
L is highly imbalanced (55.2%)Imbalance
.4 is highly imbalanced (53.7%)Imbalance
.5 is highly imbalanced (73.1%)Imbalance
is highly imbalanced (94.4%)Imbalance
.7 is highly imbalanced (73.1%)Imbalance
.8 is highly imbalanced (86.6%)Imbalance
.9 is highly imbalanced (61.4%)Imbalance
is highly imbalanced (51.2%)Imbalance
1 is highly imbalanced (69.3%)Imbalance
.10 is highly imbalanced (67.7%)Imbalance
.11 is highly imbalanced (90.4%)Imbalance
.12 is highly imbalanced (62.4%)Imbalance
.1 is highly imbalanced (74.3%)Imbalance
is highly imbalanced (81.6%)Imbalance
is highly imbalanced (82.1%)Imbalance
.13 is highly imbalanced (73.3%)Imbalance
.14 is highly imbalanced (83.2%)Imbalance
1 is uniformly distributedUniform
1 is uniformly distributedUniform
1 has unique valuesUnique
+01 05 20.4 has unique valuesUnique
000.00091185 has unique valuesUnique
+01.08901332 has unique valuesUnique
1 has unique valuesUnique

Reproduction

Analysis started2023-07-19 23:24:17.785447
Analysis finished2023-07-19 23:24:22.878661
Duration5.09 seconds
Software versionydata-profiling vv4.3.2
Download configurationconfig.json

Variables

H
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
H
1000 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowH
2nd rowH
3rd rowH
4th rowH
5th rowH

Common Values

ValueCountFrequency (%)
H 1000
100.0%

Length

2023-07-19T17:24:22.909093image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:22.955264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
h 1000
100.0%

Most occurring characters

ValueCountFrequency (%)
H 1000
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
H 1000
100.0%

1
Real number (ℝ)

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean501.83
Minimum2
Maximum1002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:22.999683image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile51.95
Q1251.75
median501.5
Q3752.25
95-th percentile952.05
Maximum1002
Range1000
Interquartile range (IQR)500.5

Descriptive statistics

Standard deviation289.20271
Coefficient of variation (CV)0.57629618
Kurtosis-1.2006742
Mean501.83
Median Absolute Deviation (MAD)250.5
Skewness0.0015632785
Sum501830
Variance83638.209
MonotonicityNot monotonic
2023-07-19T17:24:23.059606image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1
 
0.1%
674 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
663 1
 
0.1%
662 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
667 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
11 1
0.1%
ValueCountFrequency (%)
1002 1
0.1%
1001 1
0.1%
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%
995 1
0.1%
994 1
0.1%
993 1
0.1%


Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
901 
H
98 
T
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters3
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
901
90.1%
H 98
 
9.8%
T 1
 
0.1%

Length

2023-07-19T17:24:23.109847image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:23.155328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
h 98
99.0%
t 1
 
1.0%

Most occurring characters

ValueCountFrequency (%)
901
90.1%
H 98
 
9.8%
T 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 901
90.1%
Uppercase Letter 99
 
9.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 98
99.0%
T 1
 
1.0%
Space Separator
ValueCountFrequency (%)
901
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 901
90.1%
Latin 99
 
9.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 98
99.0%
T 1
 
1.0%
Common
ValueCountFrequency (%)
901
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
901
90.1%
H 98
 
9.8%
T 1
 
0.1%
Distinct990
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:23.386931image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique980 ?
Unique (%)98.0%

Sample

1st row00 00 00.91
2nd row00 00 01.20
3rd row00 00 02.01
4th row00 00 02.39
5th row00 00 04.35
ValueCountFrequency (%)
00 1082
36.1%
04 94
 
3.1%
05 90
 
3.0%
02 84
 
2.8%
10 84
 
2.8%
09 83
 
2.8%
08 79
 
2.6%
06 77
 
2.6%
03 75
 
2.5%
11 74
 
2.5%
Other values (925) 1178
39.3%
2023-07-19T17:24:23.698947image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3481
31.6%
2000
18.2%
. 1000
 
9.1%
1 811
 
7.4%
2 591
 
5.4%
4 558
 
5.1%
3 526
 
4.8%
5 523
 
4.8%
6 392
 
3.6%
8 387
 
3.5%
Other values (2) 731
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8000
72.7%
Space Separator 2000
 
18.2%
Other Punctuation 1000
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3481
43.5%
1 811
 
10.1%
2 591
 
7.4%
4 558
 
7.0%
3 526
 
6.6%
5 523
 
6.5%
6 392
 
4.9%
8 387
 
4.8%
9 385
 
4.8%
7 346
 
4.3%
Space Separator
ValueCountFrequency (%)
2000
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3481
31.6%
2000
18.2%
. 1000
 
9.1%
1 811
 
7.4%
2 591
 
5.4%
4 558
 
5.1%
3 526
 
4.8%
5 523
 
4.8%
6 392
 
3.6%
8 387
 
3.5%
Other values (2) 731
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3481
31.6%
2000
18.2%
. 1000
 
9.1%
1 811
 
7.4%
2 591
 
5.4%
4 558
 
5.1%
3 526
 
4.8%
5 523
 
4.8%
6 392
 
3.6%
8 387
 
3.5%
Other values (2) 731
 
6.6%

+01 05 20.4
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:23.954361image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11000
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row-19 29 55.8
2nd row+38 51 33.4
3rd row-51 53 36.8
4th row-40 35 28.4
5th row+03 56 47.4
ValueCountFrequency (%)
49 46
 
1.5%
08 39
 
1.3%
16 38
 
1.3%
13 37
 
1.2%
40 37
 
1.2%
50 36
 
1.2%
42 36
 
1.2%
28 36
 
1.2%
29 36
 
1.2%
10 35
 
1.2%
Other values (558) 2624
87.5%
2023-07-19T17:24:24.249919image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2000
18.2%
. 1000
9.1%
2 914
8.3%
0 894
8.1%
5 871
7.9%
1 865
7.9%
4 862
7.8%
3 858
7.8%
- 504
 
4.6%
+ 496
 
4.5%
Other values (4) 1736
15.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7000
63.6%
Space Separator 2000
 
18.2%
Other Punctuation 1000
 
9.1%
Dash Punctuation 504
 
4.6%
Math Symbol 496
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 914
13.1%
0 894
12.8%
5 871
12.4%
1 865
12.4%
4 862
12.3%
3 858
12.3%
6 493
7.0%
7 430
6.1%
8 424
6.1%
9 389
5.6%
Space Separator
ValueCountFrequency (%)
2000
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 504
100.0%
Math Symbol
ValueCountFrequency (%)
+ 496
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2000
18.2%
. 1000
9.1%
2 914
8.3%
0 894
8.1%
5 871
7.9%
1 865
7.9%
4 862
7.8%
3 858
7.8%
- 504
 
4.6%
+ 496
 
4.5%
Other values (4) 1736
15.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2000
18.2%
. 1000
9.1%
2 914
8.3%
0 894
8.1%
5 871
7.9%
1 865
7.9%
4 862
7.8%
3 858
7.8%
- 504
 
4.6%
+ 496
 
4.5%
Other values (4) 1736
15.8%

9.10
Real number (ℝ)

HIGH CORRELATION 

Distinct425
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.41304
Minimum2.07
Maximum12.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:24.335949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.07
5-th percentile6.2195
Q17.7
median8.495
Q39.12
95-th percentile10.5105
Maximum12.43
Range10.36
Interquartile range (IQR)1.42

Descriptive statistics

Standard deviation1.2868948
Coefficient of variation (CV)0.1529643
Kurtosis1.5673491
Mean8.41304
Median Absolute Deviation (MAD)0.715
Skewness-0.26062478
Sum8413.04
Variance1.6560983
MonotonicityNot monotonic
2023-07-19T17:24:24.396663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.55 10
 
1.0%
8.97 9
 
0.9%
8.56 9
 
0.9%
7.78 7
 
0.7%
8.6 7
 
0.7%
8.44 7
 
0.7%
8.85 7
 
0.7%
8.24 7
 
0.7%
8.69 7
 
0.7%
8.15 7
 
0.7%
Other values (415) 923
92.3%
ValueCountFrequency (%)
2.07 1
0.1%
2.28 1
0.1%
3.88 1
0.1%
4.37 1
0.1%
4.55 1
0.1%
4.61 1
0.1%
4.78 1
0.1%
4.89 1
0.1%
4.99 1
0.1%
5.01 1
0.1%
ValueCountFrequency (%)
12.43 1
0.1%
12.31 1
0.1%
12.19 1
0.1%
12.17 1
0.1%
12.14 1
0.1%
12.04 2
0.2%
11.99 1
0.1%
11.8 1
0.1%
11.79 1
0.1%
11.73 1
0.1%

.1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
904 
2
 
52
1
 
32
3
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
904
90.4%
2 52
 
5.2%
1 32
 
3.2%
3 12
 
1.2%

Length

2023-07-19T17:24:24.446733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:24.492647image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 52
54.2%
1 32
33.3%
3 12
 
12.5%

Most occurring characters

ValueCountFrequency (%)
904
90.4%
2 52
 
5.2%
1 32
 
3.2%
3 12
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 904
90.4%
Decimal Number 96
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 52
54.2%
1 32
33.3%
3 12
 
12.5%
Space Separator
ValueCountFrequency (%)
904
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
904
90.4%
2 52
 
5.2%
1 32
 
3.2%
3 12
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
904
90.4%
2 52
 
5.2%
1 32
 
3.2%
3 12
 
1.2%

H.1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
H
776 
G
223 
T
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowG
2nd rowG
3rd rowH
4th rowH
5th rowG

Common Values

ValueCountFrequency (%)
H 776
77.6%
G 223
 
22.3%
T 1
 
0.1%

Length

2023-07-19T17:24:24.531761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:24.576890image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
h 776
77.6%
g 223
 
22.3%
t 1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
H 776
77.6%
G 223
 
22.3%
T 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 776
77.6%
G 223
 
22.3%
T 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 776
77.6%
G 223
 
22.3%
T 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
H 776
77.6%
G 223
 
22.3%
T 1
 
0.1%

000.00091185
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:24.744374image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row000.00379737
2nd row000.00500795
3rd row000.00838170
4th row000.00996534
5th row000.01814144
ValueCountFrequency (%)
000.00379737 1
 
0.1%
000.05030890 1
 
0.1%
000.09858375 1
 
0.1%
000.09809390 1
 
0.1%
000.00838170 1
 
0.1%
000.00996534 1
 
0.1%
000.01814144 1
 
0.1%
000.02254891 1
 
0.1%
000.02729160 1
 
0.1%
000.03534189 1
 
0.1%
Other values (989) 989
99.0%
2023-07-19T17:24:24.990781image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3141
26.2%
1 1169
 
9.7%
2 1161
 
9.7%
. 999
 
8.3%
3 846
 
7.0%
6 810
 
6.8%
5 801
 
6.7%
9 776
 
6.5%
8 769
 
6.4%
7 759
 
6.3%
Other values (2) 769
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10989
91.6%
Other Punctuation 999
 
8.3%
Space Separator 12
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3141
28.6%
1 1169
 
10.6%
2 1161
 
10.6%
3 846
 
7.7%
6 810
 
7.4%
5 801
 
7.3%
9 776
 
7.1%
8 769
 
7.0%
7 759
 
6.9%
4 757
 
6.9%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3141
26.2%
1 1169
 
9.7%
2 1161
 
9.7%
. 999
 
8.3%
3 846
 
7.0%
6 810
 
6.8%
5 801
 
6.7%
9 776
 
6.5%
8 769
 
6.4%
7 759
 
6.3%
Other values (2) 769
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3141
26.2%
1 1169
 
9.7%
2 1161
 
9.7%
. 999
 
8.3%
3 846
 
7.0%
6 810
 
6.8%
5 801
 
6.7%
9 776
 
6.5%
8 769
 
6.4%
7 759
 
6.3%
Other values (2) 769
 
6.4%

+01.08901332
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:25.244081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12000
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row-19.49883745
2nd row+38.85928608
3rd row-51.89354612
4th row-40.59122440
5th row+03.94648893
ValueCountFrequency (%)
19.49883745 1
 
0.1%
50.79117384 1
 
0.1%
51.93949050 1
 
0.1%
02.67547768 1
 
0.1%
51.89354612 1
 
0.1%
40.59122440 1
 
0.1%
03.94648893 1
 
0.1%
20.03660216 1
 
0.1%
25.88647445 1
 
0.1%
36.58593777 1
 
0.1%
Other values (989) 989
99.0%
2023-07-19T17:24:25.543199image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1114
9.3%
3 1029
8.6%
1 1018
8.5%
5 1018
8.5%
0 1010
8.4%
6 1009
8.4%
4 1002
8.3%
. 999
8.3%
7 982
8.2%
8 930
7.8%
Other values (4) 1889
15.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9990
83.2%
Other Punctuation 999
 
8.3%
Dash Punctuation 504
 
4.2%
Math Symbol 495
 
4.1%
Space Separator 12
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1114
11.2%
3 1029
10.3%
1 1018
10.2%
5 1018
10.2%
0 1010
10.1%
6 1009
10.1%
4 1002
10.0%
7 982
9.8%
8 930
9.3%
9 878
8.8%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 504
100.0%
Math Symbol
ValueCountFrequency (%)
+ 495
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1114
9.3%
3 1029
8.6%
1 1018
8.5%
5 1018
8.5%
0 1010
8.4%
6 1009
8.4%
4 1002
8.3%
. 999
8.3%
7 982
8.2%
8 930
7.8%
Other values (4) 1889
15.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1114
9.3%
3 1029
8.6%
1 1018
8.5%
5 1018
8.5%
0 1010
8.4%
6 1009
8.4%
4 1002
8.3%
. 999
8.3%
7 982
8.2%
8 930
7.8%
Other values (4) 1889
15.7%

.2
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
877 
A
 
82
*
 
27
B
 
9
+
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters6
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row+
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
877
87.7%
A 82
 
8.2%
* 27
 
2.7%
B 9
 
0.9%
+ 4
 
0.4%
C 1
 
0.1%

Length

2023-07-19T17:24:25.619562image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:25.668994image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
a 82
66.7%
31
 
25.2%
b 9
 
7.3%
c 1
 
0.8%

Most occurring characters

ValueCountFrequency (%)
877
87.7%
A 82
 
8.2%
* 27
 
2.7%
B 9
 
0.9%
+ 4
 
0.4%
C 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 877
87.7%
Uppercase Letter 92
 
9.2%
Other Punctuation 27
 
2.7%
Math Symbol 4
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 82
89.1%
B 9
 
9.8%
C 1
 
1.1%
Space Separator
ValueCountFrequency (%)
877
100.0%
Other Punctuation
ValueCountFrequency (%)
* 27
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 908
90.8%
Latin 92
 
9.2%

Most frequent character per script

Common
ValueCountFrequency (%)
877
96.6%
* 27
 
3.0%
+ 4
 
0.4%
Latin
ValueCountFrequency (%)
A 82
89.1%
B 9
 
9.8%
C 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
877
87.7%
A 82
 
8.2%
* 27
 
2.7%
B 9
 
0.9%
+ 4
 
0.4%
C 1
 
0.1%

3.54
Text

Distinct745
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:25.902401image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique559 ?
Unique (%)55.9%

Sample

1st row 21.90
2nd row 2.81
3rd row 7.75
4th row 2.87
5th row 18.80
ValueCountFrequency (%)
4.21 6
 
0.6%
2.91 5
 
0.5%
4.41 5
 
0.5%
2.46 5
 
0.5%
3.49 5
 
0.5%
5.84 4
 
0.4%
2.92 4
 
0.4%
1.62 4
 
0.4%
4.78 4
 
0.4%
2.89 4
 
0.4%
Other values (722) 953
95.4%
2023-07-19T17:24:26.208502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2763
39.5%
. 999
 
14.3%
1 473
 
6.8%
2 370
 
5.3%
3 337
 
4.8%
4 333
 
4.8%
5 315
 
4.5%
0 296
 
4.2%
6 289
 
4.1%
8 275
 
3.9%
Other values (3) 550
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3212
45.9%
Space Separator 2763
39.5%
Other Punctuation 999
 
14.3%
Dash Punctuation 26
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 473
14.7%
2 370
11.5%
3 337
10.5%
4 333
10.4%
5 315
9.8%
0 296
9.2%
6 289
9.0%
8 275
8.6%
9 262
8.2%
7 262
8.2%
Space Separator
ValueCountFrequency (%)
2763
100.0%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2763
39.5%
. 999
 
14.3%
1 473
 
6.8%
2 370
 
5.3%
3 337
 
4.8%
4 333
 
4.8%
5 315
 
4.5%
0 296
 
4.2%
6 289
 
4.1%
8 275
 
3.9%
Other values (3) 550
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2763
39.5%
. 999
 
14.3%
1 473
 
6.8%
2 370
 
5.3%
3 337
 
4.8%
4 333
 
4.8%
5 315
 
4.5%
0 296
 
4.2%
6 289
 
4.1%
8 275
 
3.9%
Other values (3) 550
 
7.9%

-5.20
Text

Distinct949
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:26.480063image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique900 ?
Unique (%)90.0%

Sample

1st row 181.21
2nd row 5.24
3rd row 62.85
4th row 2.53
5th row 226.29
ValueCountFrequency (%)
15.17 3
 
0.3%
3.01 3
 
0.3%
8.65 3
 
0.3%
7.17 3
 
0.3%
5.33 3
 
0.3%
0.01 3
 
0.3%
39.43 2
 
0.2%
3.67 2
 
0.2%
10.40 2
 
0.2%
34.46 2
 
0.2%
Other values (904) 973
97.4%
2023-07-19T17:24:26.890488image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2822
35.3%
. 999
 
12.5%
1 598
 
7.5%
2 504
 
6.3%
3 407
 
5.1%
4 370
 
4.6%
0 356
 
4.5%
- 342
 
4.3%
5 339
 
4.2%
9 318
 
4.0%
Other values (3) 945
 
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3837
48.0%
Space Separator 2822
35.3%
Other Punctuation 999
 
12.5%
Dash Punctuation 342
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 598
15.6%
2 504
13.1%
3 407
10.6%
4 370
9.6%
0 356
9.3%
5 339
8.8%
9 318
8.3%
7 317
8.3%
6 315
8.2%
8 313
8.2%
Space Separator
ValueCountFrequency (%)
2822
100.0%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 342
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2822
35.3%
. 999
 
12.5%
1 598
 
7.5%
2 504
 
6.3%
3 407
 
5.1%
4 370
 
4.6%
0 356
 
4.5%
- 342
 
4.3%
5 339
 
4.2%
9 318
 
4.0%
Other values (3) 945
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2822
35.3%
. 999
 
12.5%
1 598
 
7.5%
2 504
 
6.3%
3 407
 
5.1%
4 370
 
4.6%
0 356
 
4.5%
- 342
 
4.3%
5 339
 
4.2%
9 318
 
4.0%
Other values (3) 945
 
11.8%

-1.88
Text

Distinct936
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:27.158730image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique881 ?
Unique (%)88.1%

Sample

1st row -0.93
2nd row -2.91
3rd row 0.16
4th row 9.07
5th row -12.84
ValueCountFrequency (%)
8.04 4
 
0.4%
6.51 4
 
0.4%
0.90 4
 
0.4%
2.43 4
 
0.4%
3.02 3
 
0.3%
8.15 3
 
0.3%
0.10 3
 
0.3%
0.93 3
 
0.3%
11.88 3
 
0.3%
1.36 3
 
0.3%
Other values (874) 965
96.6%
2023-07-19T17:24:27.470485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2687
33.6%
. 999
 
12.5%
- 715
 
8.9%
1 583
 
7.3%
2 438
 
5.5%
3 377
 
4.7%
4 351
 
4.4%
7 329
 
4.1%
5 326
 
4.1%
0 324
 
4.0%
Other values (3) 871
 
10.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3599
45.0%
Space Separator 2687
33.6%
Other Punctuation 999
 
12.5%
Dash Punctuation 715
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 583
16.2%
2 438
12.2%
3 377
10.5%
4 351
9.8%
7 329
9.1%
5 326
9.1%
0 324
9.0%
6 301
8.4%
8 292
8.1%
9 278
7.7%
Space Separator
ValueCountFrequency (%)
2687
100.0%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 715
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2687
33.6%
. 999
 
12.5%
- 715
 
8.9%
1 583
 
7.3%
2 438
 
5.5%
3 377
 
4.7%
4 351
 
4.4%
7 329
 
4.1%
5 326
 
4.1%
0 324
 
4.0%
Other values (3) 871
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2687
33.6%
. 999
 
12.5%
- 715
 
8.9%
1 583
 
7.3%
2 438
 
5.5%
3 377
 
4.7%
4 351
 
4.4%
7 329
 
4.1%
5 326
 
4.1%
0 324
 
4.0%
Other values (3) 871
 
10.9%

1.32
Text

Distinct206
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:27.660585image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)7.9%

Sample

1st row 1.28
2nd row 0.53
3rd row 0.53
4th row 0.64
5th row 4.03
ValueCountFrequency (%)
0.79 19
 
1.9%
0.64 18
 
1.8%
0.78 18
 
1.8%
0.67 17
 
1.7%
0.68 17
 
1.7%
0.66 17
 
1.7%
0.86 16
 
1.6%
0.87 15
 
1.5%
0.61 15
 
1.5%
0.76 15
 
1.5%
Other values (195) 832
83.3%
2023-07-19T17:24:27.889789image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1994
33.2%
. 999
16.7%
0 828
13.8%
1 470
 
7.8%
6 278
 
4.6%
7 267
 
4.5%
8 237
 
4.0%
5 206
 
3.4%
9 203
 
3.4%
4 190
 
3.2%
Other values (2) 328
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3007
50.1%
Space Separator 1994
33.2%
Other Punctuation 999
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 828
27.5%
1 470
15.6%
6 278
 
9.2%
7 267
 
8.9%
8 237
 
7.9%
5 206
 
6.9%
9 203
 
6.8%
4 190
 
6.3%
2 186
 
6.2%
3 142
 
4.7%
Space Separator
ValueCountFrequency (%)
1994
100.0%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1994
33.2%
. 999
16.7%
0 828
13.8%
1 470
 
7.8%
6 278
 
4.6%
7 267
 
4.5%
8 237
 
4.0%
5 206
 
3.4%
9 203
 
3.4%
4 190
 
3.2%
Other values (2) 328
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1994
33.2%
. 999
16.7%
0 828
13.8%
1 470
 
7.8%
6 278
 
4.6%
7 267
 
4.5%
8 237
 
4.0%
5 206
 
3.4%
9 203
 
3.4%
4 190
 
3.2%
Other values (2) 328
 
5.5%

0.74
Text

Distinct162
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:28.064956image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)7.1%

Sample

1st row 0.70
2nd row 0.40
3rd row 0.59
4th row 0.61
5th row 2.18
ValueCountFrequency (%)
0.60 30
 
3.0%
0.64 27
 
2.7%
0.68 27
 
2.7%
0.58 27
 
2.7%
0.59 27
 
2.7%
0.55 26
 
2.6%
0.63 26
 
2.6%
0.51 23
 
2.3%
0.54 23
 
2.3%
0.48 22
 
2.2%
Other values (151) 741
74.2%
2023-07-19T17:24:28.282135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1995
33.2%
. 999
16.7%
0 975
16.2%
6 347
 
5.8%
5 341
 
5.7%
4 248
 
4.1%
7 226
 
3.8%
1 224
 
3.7%
8 196
 
3.3%
9 158
 
2.6%
Other values (2) 291
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3006
50.1%
Space Separator 1995
33.2%
Other Punctuation 999
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 975
32.4%
6 347
 
11.5%
5 341
 
11.3%
4 248
 
8.3%
7 226
 
7.5%
1 224
 
7.5%
8 196
 
6.5%
9 158
 
5.3%
2 150
 
5.0%
3 141
 
4.7%
Space Separator
ValueCountFrequency (%)
1995
100.0%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1995
33.2%
. 999
16.7%
0 975
16.2%
6 347
 
5.8%
5 341
 
5.7%
4 248
 
4.1%
7 226
 
3.8%
1 224
 
3.7%
8 196
 
3.3%
9 158
 
2.6%
Other values (2) 291
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1995
33.2%
. 999
16.7%
0 975
16.2%
6 347
 
5.8%
5 341
 
5.7%
4 248
 
4.1%
7 226
 
3.8%
1 224
 
3.7%
8 196
 
3.3%
9 158
 
2.6%
Other values (2) 291
 
4.9%

1.39
Text

Distinct217
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:28.469754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)8.9%

Sample

1st row 3.10
2nd row 0.63
3rd row 0.97
4th row 1.11
5th row 4.99
ValueCountFrequency (%)
0.94 18
 
1.8%
0.87 17
 
1.7%
0.97 16
 
1.6%
0.93 16
 
1.6%
1.10 16
 
1.6%
0.92 15
 
1.5%
0.82 15
 
1.5%
1.11 15
 
1.5%
1.18 15
 
1.5%
1.17 15
 
1.5%
Other values (206) 841
84.2%
2023-07-19T17:24:28.698735image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1999
33.3%
. 999
16.7%
1 774
 
12.9%
0 623
 
10.4%
2 241
 
4.0%
9 240
 
4.0%
7 223
 
3.7%
8 212
 
3.5%
3 194
 
3.2%
4 191
 
3.2%
Other values (2) 304
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3002
50.0%
Space Separator 1999
33.3%
Other Punctuation 999
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 774
25.8%
0 623
20.8%
2 241
 
8.0%
9 240
 
8.0%
7 223
 
7.4%
8 212
 
7.1%
3 194
 
6.5%
4 191
 
6.4%
6 164
 
5.5%
5 140
 
4.7%
Space Separator
ValueCountFrequency (%)
1999
100.0%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1999
33.3%
. 999
16.7%
1 774
 
12.9%
0 623
 
10.4%
2 241
 
4.0%
9 240
 
4.0%
7 223
 
3.7%
8 212
 
3.5%
3 194
 
3.2%
4 191
 
3.2%
Other values (2) 304
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1999
33.3%
. 999
16.7%
1 774
 
12.9%
0 623
 
10.4%
2 241
 
4.0%
9 240
 
4.0%
7 223
 
3.7%
8 212
 
3.5%
3 194
 
3.2%
4 191
 
3.2%
Other values (2) 304
 
5.1%

1.36
Text

Distinct226
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:28.907852image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)7.5%

Sample

1st row 1.74
2nd row 0.57
3rd row 0.65
4th row 0.67
5th row 6.15
ValueCountFrequency (%)
0.74 18
 
1.8%
0.71 17
 
1.7%
0.84 16
 
1.6%
0.82 16
 
1.6%
0.89 15
 
1.5%
0.88 14
 
1.4%
0.78 13
 
1.3%
0.72 13
 
1.3%
1.18 13
 
1.3%
0.70 13
 
1.3%
Other values (215) 851
85.2%
2023-07-19T17:24:29.164159image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1997
33.3%
. 999
16.7%
0 690
 
11.5%
1 623
 
10.4%
8 273
 
4.5%
7 241
 
4.0%
2 222
 
3.7%
6 219
 
3.6%
5 200
 
3.3%
9 196
 
3.3%
Other values (2) 340
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3004
50.1%
Space Separator 1997
33.3%
Other Punctuation 999
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 690
23.0%
1 623
20.7%
8 273
 
9.1%
7 241
 
8.0%
2 222
 
7.4%
6 219
 
7.3%
5 200
 
6.7%
9 196
 
6.5%
4 186
 
6.2%
3 154
 
5.1%
Space Separator
ValueCountFrequency (%)
1997
100.0%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1997
33.3%
. 999
16.7%
0 690
 
11.5%
1 623
 
10.4%
8 273
 
4.5%
7 241
 
4.0%
2 222
 
3.7%
6 219
 
3.6%
5 200
 
3.3%
9 196
 
3.3%
Other values (2) 340
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1997
33.3%
. 999
16.7%
0 690
 
11.5%
1 623
 
10.4%
8 273
 
4.5%
7 241
 
4.0%
2 222
 
3.7%
6 219
 
3.6%
5 200
 
3.3%
9 196
 
3.3%
Other values (2) 340
 
5.7%

0.81
Text

Distinct170
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:29.334600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)6.7%

Sample

1st row 0.92
2nd row 0.47
3rd row 0.65
4th row 0.74
5th row 3.20
ValueCountFrequency (%)
0.68 28
 
2.8%
0.64 25
 
2.5%
0.67 24
 
2.4%
0.65 23
 
2.3%
0.76 22
 
2.2%
0.56 22
 
2.2%
0.71 22
 
2.2%
0.57 21
 
2.1%
0.61 21
 
2.1%
0.59 21
 
2.1%
Other values (159) 770
77.1%
2023-07-19T17:24:29.547426image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1999
33.3%
. 999
16.7%
0 932
15.5%
6 336
 
5.6%
1 316
 
5.3%
5 288
 
4.8%
7 279
 
4.7%
8 201
 
3.4%
4 192
 
3.2%
9 183
 
3.0%
Other values (2) 275
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3002
50.0%
Space Separator 1999
33.3%
Other Punctuation 999
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 932
31.0%
6 336
 
11.2%
1 316
 
10.5%
5 288
 
9.6%
7 279
 
9.3%
8 201
 
6.7%
4 192
 
6.4%
9 183
 
6.1%
2 155
 
5.2%
3 120
 
4.0%
Space Separator
ValueCountFrequency (%)
1999
100.0%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1999
33.3%
. 999
16.7%
0 932
15.5%
6 336
 
5.6%
1 316
 
5.3%
5 288
 
4.8%
7 279
 
4.7%
8 201
 
3.4%
4 192
 
3.2%
9 183
 
3.0%
Other values (2) 275
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1999
33.3%
. 999
16.7%
0 932
15.5%
6 336
 
5.6%
1 316
 
5.3%
5 288
 
4.8%
7 279
 
4.7%
8 201
 
3.4%
4 192
 
3.2%
9 183
 
3.0%
Other values (2) 275
 
4.6%

0.32
Text

Distinct102
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:29.685193image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)1.3%

Sample

1st row 0.12
2nd row 0.06
3rd row-0.22
4th row 0.10
5th row 0.35
ValueCountFrequency (%)
0.03 50
 
5.0%
0.02 48
 
4.8%
0.06 42
 
4.2%
0.07 39
 
3.9%
0.04 39
 
3.9%
0.08 39
 
3.9%
0.05 37
 
3.7%
0.01 37
 
3.7%
0.14 34
 
3.4%
0.13 33
 
3.3%
Other values (46) 601
60.2%
2023-07-19T17:24:29.866471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1475
29.5%
. 999
20.0%
621
12.4%
1 387
 
7.7%
- 383
 
7.7%
2 289
 
5.8%
3 229
 
4.6%
4 167
 
3.3%
5 111
 
2.2%
8 98
 
2.0%
Other values (3) 241
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2997
59.9%
Other Punctuation 999
 
20.0%
Space Separator 621
 
12.4%
Dash Punctuation 383
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1475
49.2%
1 387
 
12.9%
2 289
 
9.6%
3 229
 
7.6%
4 167
 
5.6%
5 111
 
3.7%
8 98
 
3.3%
6 91
 
3.0%
7 88
 
2.9%
9 62
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Space Separator
ValueCountFrequency (%)
621
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 383
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1475
29.5%
. 999
20.0%
621
12.4%
1 387
 
7.7%
- 383
 
7.7%
2 289
 
5.8%
3 229
 
4.6%
4 167
 
3.3%
5 111
 
2.2%
8 98
 
2.0%
Other values (3) 241
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1475
29.5%
. 999
20.0%
621
12.4%
1 387
 
7.7%
- 383
 
7.7%
2 289
 
5.8%
3 229
 
4.6%
4 167
 
3.3%
5 111
 
2.2%
8 98
 
2.0%
Other values (3) 241
 
4.8%

-0.07
Text

Distinct75
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:29.993377image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)1.1%

Sample

1st row-0.14
2nd row 0.09
3rd row-0.09
4th row 0.24
5th row-0.01
ValueCountFrequency (%)
0.06 70
 
7.0%
0.04 63
 
6.3%
0.02 62
 
6.2%
0.03 56
 
5.6%
0.10 54
 
5.4%
0.05 50
 
5.0%
0.09 48
 
4.8%
0.01 47
 
4.7%
0.07 47
 
4.7%
0.12 39
 
3.9%
Other values (35) 463
46.3%
2023-07-19T17:24:30.166928image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1624
32.5%
. 999
20.0%
676
13.5%
1 434
 
8.7%
- 328
 
6.6%
2 244
 
4.9%
3 137
 
2.7%
4 118
 
2.4%
6 114
 
2.3%
5 105
 
2.1%
Other values (3) 221
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2997
59.9%
Other Punctuation 999
 
20.0%
Space Separator 676
 
13.5%
Dash Punctuation 328
 
6.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1624
54.2%
1 434
 
14.5%
2 244
 
8.1%
3 137
 
4.6%
4 118
 
3.9%
6 114
 
3.8%
5 105
 
3.5%
7 81
 
2.7%
9 73
 
2.4%
8 67
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Space Separator
ValueCountFrequency (%)
676
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 328
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1624
32.5%
. 999
20.0%
676
13.5%
1 434
 
8.7%
- 328
 
6.6%
2 244
 
4.9%
3 137
 
2.7%
4 118
 
2.4%
6 114
 
2.3%
5 105
 
2.1%
Other values (3) 221
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1624
32.5%
. 999
20.0%
676
13.5%
1 434
 
8.7%
- 328
 
6.6%
2 244
 
4.9%
3 137
 
2.7%
4 118
 
2.4%
6 114
 
2.3%
5 105
 
2.1%
Other values (3) 221
 
4.4%

-0.11
Text

Distinct85
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:30.298045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)1.3%

Sample

1st row-0.24
2nd row 0.04
3rd row-0.03
4th row 0.06
5th row 0.03
ValueCountFrequency (%)
0.06 58
 
5.8%
0.12 55
 
5.5%
0.01 54
 
5.4%
0.03 54
 
5.4%
0.09 53
 
5.3%
0.02 45
 
4.5%
0.04 45
 
4.5%
0.08 42
 
4.2%
0.13 41
 
4.1%
0.07 40
 
4.0%
Other values (35) 512
51.3%
2023-07-19T17:24:30.469915image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1538
30.8%
. 999
20.0%
522
 
10.4%
- 482
 
9.6%
1 451
 
9.0%
2 295
 
5.9%
3 170
 
3.4%
4 109
 
2.2%
6 100
 
2.0%
9 89
 
1.8%
Other values (3) 245
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2997
59.9%
Other Punctuation 999
 
20.0%
Space Separator 522
 
10.4%
Dash Punctuation 482
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1538
51.3%
1 451
 
15.0%
2 295
 
9.8%
3 170
 
5.7%
4 109
 
3.6%
6 100
 
3.3%
9 89
 
3.0%
5 85
 
2.8%
7 84
 
2.8%
8 76
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Space Separator
ValueCountFrequency (%)
522
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 482
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1538
30.8%
. 999
20.0%
522
 
10.4%
- 482
 
9.6%
1 451
 
9.0%
2 295
 
5.9%
3 170
 
3.4%
4 109
 
2.2%
6 100
 
2.0%
9 89
 
1.8%
Other values (3) 245
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1538
30.8%
. 999
20.0%
522
 
10.4%
- 482
 
9.6%
1 451
 
9.0%
2 295
 
5.9%
3 170
 
3.4%
4 109
 
2.2%
6 100
 
2.0%
9 89
 
1.8%
Other values (3) 245
 
4.9%

-0.24
Text

Distinct111
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:30.609789image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)1.5%

Sample

1st row-0.29
2nd row 0.43
3rd row 0.24
4th row 0.26
5th row-0.11
ValueCountFrequency (%)
0.07 41
 
4.1%
0.01 40
 
4.0%
0.04 39
 
3.9%
0.02 38
 
3.8%
0.05 38
 
3.8%
0.11 37
 
3.7%
0.09 36
 
3.6%
0.10 35
 
3.5%
0.03 35
 
3.5%
0.08 33
 
3.3%
Other values (52) 627
62.8%
2023-07-19T17:24:30.794100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1456
29.1%
. 999
20.0%
- 532
 
10.6%
472
 
9.4%
1 388
 
7.8%
2 310
 
6.2%
3 200
 
4.0%
4 172
 
3.4%
5 108
 
2.2%
7 99
 
2.0%
Other values (3) 264
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2997
59.9%
Other Punctuation 999
 
20.0%
Dash Punctuation 532
 
10.6%
Space Separator 472
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1456
48.6%
1 388
 
12.9%
2 310
 
10.3%
3 200
 
6.7%
4 172
 
5.7%
5 108
 
3.6%
7 99
 
3.3%
9 95
 
3.2%
6 88
 
2.9%
8 81
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 532
100.0%
Space Separator
ValueCountFrequency (%)
472
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1456
29.1%
. 999
20.0%
- 532
 
10.6%
472
 
9.4%
1 388
 
7.8%
2 310
 
6.2%
3 200
 
4.0%
4 172
 
3.4%
5 108
 
2.2%
7 99
 
2.0%
Other values (3) 264
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1456
29.1%
. 999
20.0%
- 532
 
10.6%
472
 
9.4%
1 388
 
7.8%
2 310
 
6.2%
3 200
 
4.0%
4 172
 
3.4%
5 108
 
2.2%
7 99
 
2.0%
Other values (3) 264
 
5.3%

0.09
Text

Distinct64
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:30.912220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)1.5%

Sample

1st row 0.01
2nd row-0.01
3rd row 0.20
4th row-0.10
5th row-0.02
ValueCountFrequency (%)
0.03 90
 
9.0%
0.01 87
 
8.7%
0.02 79
 
7.9%
0.06 74
 
7.4%
0.05 73
 
7.3%
0.04 66
 
6.6%
0.07 65
 
6.5%
0.11 48
 
4.8%
0.09 45
 
4.5%
0.10 43
 
4.3%
Other values (25) 329
32.9%
2023-07-19T17:24:31.069989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1757
35.1%
. 999
20.0%
555
 
11.1%
- 449
 
9.0%
1 428
 
8.6%
2 169
 
3.4%
3 123
 
2.5%
4 108
 
2.2%
5 105
 
2.1%
6 101
 
2.0%
Other values (3) 206
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2997
59.9%
Other Punctuation 999
 
20.0%
Space Separator 555
 
11.1%
Dash Punctuation 449
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1757
58.6%
1 428
 
14.3%
2 169
 
5.6%
3 123
 
4.1%
4 108
 
3.6%
5 105
 
3.5%
6 101
 
3.4%
7 79
 
2.6%
9 68
 
2.3%
8 59
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Space Separator
ValueCountFrequency (%)
555
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 449
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1757
35.1%
. 999
20.0%
555
 
11.1%
- 449
 
9.0%
1 428
 
8.6%
2 169
 
3.4%
3 123
 
2.5%
4 108
 
2.2%
5 105
 
2.1%
6 101
 
2.0%
Other values (3) 206
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1757
35.1%
. 999
20.0%
555
 
11.1%
- 449
 
9.0%
1 428
 
8.6%
2 169
 
3.4%
3 123
 
2.5%
4 108
 
2.2%
5 105
 
2.1%
6 101
 
2.0%
Other values (3) 206
 
4.1%

-0.01
Text

Distinct82
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:31.204076image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)1.1%

Sample

1st row 0.21
2nd row-0.06
3rd row 0.08
4th row 0.20
5th row 0.47
ValueCountFrequency (%)
0.02 61
 
6.1%
0.01 57
 
5.7%
0.07 56
 
5.6%
0.04 51
 
5.1%
0.03 50
 
5.0%
0.11 45
 
4.5%
0.06 45
 
4.5%
0.08 44
 
4.4%
0.05 44
 
4.4%
0.09 43
 
4.3%
Other values (45) 503
50.4%
2023-07-19T17:24:31.384042image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1570
31.4%
. 999
20.0%
689
13.8%
1 442
 
8.8%
- 315
 
6.3%
2 263
 
5.3%
3 150
 
3.0%
4 129
 
2.6%
7 103
 
2.1%
5 100
 
2.0%
Other values (3) 240
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2997
59.9%
Other Punctuation 999
 
20.0%
Space Separator 689
 
13.8%
Dash Punctuation 315
 
6.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1570
52.4%
1 442
 
14.7%
2 263
 
8.8%
3 150
 
5.0%
4 129
 
4.3%
7 103
 
3.4%
5 100
 
3.3%
6 93
 
3.1%
9 75
 
2.5%
8 72
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Space Separator
ValueCountFrequency (%)
689
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 315
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1570
31.4%
. 999
20.0%
689
13.8%
1 442
 
8.8%
- 315
 
6.3%
2 263
 
5.3%
3 150
 
3.0%
4 129
 
2.6%
7 103
 
2.1%
5 100
 
2.0%
Other values (3) 240
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1570
31.4%
. 999
20.0%
689
13.8%
1 442
 
8.8%
- 315
 
6.3%
2 263
 
5.3%
3 150
 
3.0%
4 129
 
2.6%
7 103
 
2.1%
5 100
 
2.0%
Other values (3) 240
 
4.8%

0.10
Text

Distinct62
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:31.500814image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.8%

Sample

1st row-0.02
2nd row 0.03
3rd row 0.18
4th row-0.16
5th row-0.02
ValueCountFrequency (%)
0.01 87
 
8.7%
0.03 86
 
8.6%
0.02 82
 
8.2%
0.04 75
 
7.5%
0.05 70
 
7.0%
0.07 65
 
6.5%
0.06 64
 
6.4%
0.08 50
 
5.0%
0.10 49
 
4.9%
0.00 48
 
4.8%
Other values (24) 323
32.3%
2023-07-19T17:24:31.662504image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1770
35.4%
. 999
20.0%
572
 
11.4%
- 432
 
8.6%
1 409
 
8.2%
2 176
 
3.5%
3 131
 
2.6%
4 119
 
2.4%
5 101
 
2.0%
6 93
 
1.9%
Other values (3) 198
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2997
59.9%
Other Punctuation 999
 
20.0%
Space Separator 572
 
11.4%
Dash Punctuation 432
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1770
59.1%
1 409
 
13.6%
2 176
 
5.9%
3 131
 
4.4%
4 119
 
4.0%
5 101
 
3.4%
6 93
 
3.1%
7 77
 
2.6%
8 63
 
2.1%
9 58
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Space Separator
ValueCountFrequency (%)
572
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 432
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1770
35.4%
. 999
20.0%
572
 
11.4%
- 432
 
8.6%
1 409
 
8.2%
2 176
 
3.5%
3 131
 
2.6%
4 119
 
2.4%
5 101
 
2.0%
6 93
 
1.9%
Other values (3) 198
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1770
35.4%
. 999
20.0%
572
 
11.4%
- 432
 
8.6%
1 409
 
8.2%
2 176
 
3.5%
3 131
 
2.6%
4 119
 
2.4%
5 101
 
2.0%
6 93
 
1.9%
Other values (3) 198
 
4.0%
Distinct112
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:31.800192image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)1.7%

Sample

1st row-0.19
2nd row 0.24
3rd row 0.08
4th row-0.30
5th row 0.03
ValueCountFrequency (%)
0.04 42
 
4.2%
0.02 38
 
3.8%
0.05 34
 
3.4%
0.10 32
 
3.2%
0.03 32
 
3.2%
0.01 31
 
3.1%
0.07 31
 
3.1%
0.16 29
 
2.9%
0.11 29
 
2.9%
0.26 28
 
2.8%
Other values (53) 673
67.4%
2023-07-19T17:24:31.984848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1417
28.3%
. 999
20.0%
- 611
12.2%
393
 
7.9%
1 361
 
7.2%
2 330
 
6.6%
3 247
 
4.9%
4 170
 
3.4%
5 113
 
2.3%
6 106
 
2.1%
Other values (3) 253
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2997
59.9%
Other Punctuation 999
 
20.0%
Dash Punctuation 611
 
12.2%
Space Separator 393
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1417
47.3%
1 361
 
12.0%
2 330
 
11.0%
3 247
 
8.2%
4 170
 
5.7%
5 113
 
3.8%
6 106
 
3.5%
7 93
 
3.1%
8 83
 
2.8%
9 77
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 611
100.0%
Space Separator
ValueCountFrequency (%)
393
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1417
28.3%
. 999
20.0%
- 611
12.2%
393
 
7.9%
1 361
 
7.2%
2 330
 
6.6%
3 247
 
4.9%
4 170
 
3.4%
5 113
 
2.3%
6 106
 
2.1%
Other values (3) 253
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1417
28.3%
. 999
20.0%
- 611
12.2%
393
 
7.9%
1 361
 
7.2%
2 330
 
6.6%
3 247
 
4.9%
4 170
 
3.4%
5 113
 
2.3%
6 106
 
2.1%
Other values (3) 253
 
5.1%

0.01
Text

Distinct73
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:32.113212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)1.2%

Sample

1st row-0.28
2nd row 0.07
3rd row-0.31
4th row-0.19
5th row 0.31
ValueCountFrequency (%)
0.05 58
 
5.8%
0.04 58
 
5.8%
0.01 55
 
5.5%
0.09 51
 
5.1%
0.10 48
 
4.8%
0.07 47
 
4.7%
0.02 46
 
4.6%
0.11 45
 
4.5%
0.03 44
 
4.4%
0.08 42
 
4.2%
Other values (33) 505
50.6%
2023-07-19T17:24:32.283037image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1576
31.5%
. 999
20.0%
734
14.7%
1 464
 
9.3%
- 270
 
5.4%
2 258
 
5.2%
3 128
 
2.6%
5 117
 
2.3%
4 112
 
2.2%
6 91
 
1.8%
Other values (3) 251
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2997
59.9%
Other Punctuation 999
 
20.0%
Space Separator 734
 
14.7%
Dash Punctuation 270
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1576
52.6%
1 464
 
15.5%
2 258
 
8.6%
3 128
 
4.3%
5 117
 
3.9%
4 112
 
3.7%
6 91
 
3.0%
7 91
 
3.0%
8 83
 
2.8%
9 77
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Space Separator
ValueCountFrequency (%)
734
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1576
31.5%
. 999
20.0%
734
14.7%
1 464
 
9.3%
- 270
 
5.4%
2 258
 
5.2%
3 128
 
2.6%
5 117
 
2.3%
4 112
 
2.2%
6 91
 
1.8%
Other values (3) 251
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1576
31.5%
. 999
20.0%
734
14.7%
1 464
 
9.3%
- 270
 
5.4%
2 258
 
5.2%
3 128
 
2.6%
5 117
 
2.3%
4 112
 
2.2%
6 91
 
1.8%
Other values (3) 251
 
5.0%

0.34
Text

Distinct111
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:32.426880image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)1.2%

Sample

1st row 0.14
2nd row 0.21
3rd row-0.18
4th row 0.06
5th row 0.35
ValueCountFrequency (%)
0.09 47
 
4.7%
0.05 38
 
3.8%
0.08 37
 
3.7%
0.15 36
 
3.6%
0.02 35
 
3.5%
0.07 34
 
3.4%
0.06 33
 
3.3%
0.22 32
 
3.2%
0.11 32
 
3.2%
0.04 29
 
2.9%
Other values (56) 646
64.7%
2023-07-19T17:24:32.616705image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1413
28.3%
. 999
20.0%
557
 
11.1%
- 447
 
8.9%
1 372
 
7.4%
2 310
 
6.2%
3 202
 
4.0%
4 161
 
3.2%
5 146
 
2.9%
6 113
 
2.3%
Other values (3) 280
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2997
59.9%
Other Punctuation 999
 
20.0%
Space Separator 557
 
11.1%
Dash Punctuation 447
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1413
47.1%
1 372
 
12.4%
2 310
 
10.3%
3 202
 
6.7%
4 161
 
5.4%
5 146
 
4.9%
6 113
 
3.8%
8 95
 
3.2%
9 93
 
3.1%
7 92
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 999
100.0%
Space Separator
ValueCountFrequency (%)
557
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 447
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1413
28.3%
. 999
20.0%
557
 
11.1%
- 447
 
8.9%
1 372
 
7.4%
2 310
 
6.2%
3 202
 
4.0%
4 161
 
3.2%
5 146
 
2.9%
6 113
 
2.3%
Other values (3) 280
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1413
28.3%
. 999
20.0%
557
 
11.1%
- 447
 
8.9%
1 372
 
7.4%
2 310
 
6.2%
3 202
 
4.0%
4 161
 
3.2%
5 146
 
2.9%
6 113
 
2.3%
Other values (3) 280
 
5.6%

0
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct14
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0
688 
2
121 
1
106 
3
 
34
4
 
24
Other values (9)
 
27

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3000
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row 2
2nd row 0
3rd row 0
4th row 0
5th row 4

Common Values

ValueCountFrequency (%)
0 688
68.8%
2 121
 
12.1%
1 106
 
10.6%
3 34
 
3.4%
4 24
 
2.4%
5 9
 
0.9%
7 5
 
0.5%
6 4
 
0.4%
17 2
 
0.2%
14 2
 
0.2%
Other values (4) 5
 
0.5%

Length

2023-07-19T17:24:32.686858image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 688
68.9%
2 121
 
12.1%
1 106
 
10.6%
3 34
 
3.4%
4 24
 
2.4%
5 9
 
0.9%
7 5
 
0.5%
6 4
 
0.4%
17 2
 
0.2%
14 2
 
0.2%
Other values (3) 4
 
0.4%

Most occurring characters

ValueCountFrequency (%)
1993
66.4%
0 689
 
23.0%
2 122
 
4.1%
1 114
 
3.8%
3 34
 
1.1%
4 26
 
0.9%
5 9
 
0.3%
7 7
 
0.2%
6 4
 
0.1%
8 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 1993
66.4%
Decimal Number 1007
33.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 689
68.4%
2 122
 
12.1%
1 114
 
11.3%
3 34
 
3.4%
4 26
 
2.6%
5 9
 
0.9%
7 7
 
0.7%
6 4
 
0.4%
8 2
 
0.2%
Space Separator
ValueCountFrequency (%)
1993
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1993
66.4%
0 689
 
23.0%
2 122
 
4.1%
1 114
 
3.8%
3 34
 
1.1%
4 26
 
0.9%
5 9
 
0.3%
7 7
 
0.2%
6 4
 
0.1%
8 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1993
66.4%
0 689
 
23.0%
2 122
 
4.1%
1 114
 
3.8%
3 34
 
1.1%
4 26
 
0.9%
5 9
 
0.3%
7 7
 
0.2%
6 4
 
0.1%
8 2
 
0.1%

0.74
Text

Distinct402
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:32.882776image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)14.4%

Sample

1st row 1.45
2nd row-0.45
3rd row-1.46
4th row-1.24
5th row 2.95
ValueCountFrequency (%)
0.45 13
 
1.3%
0.31 12
 
1.2%
0.42 11
 
1.1%
0.04 11
 
1.1%
0.61 11
 
1.1%
0.22 10
 
1.0%
0.24 10
 
1.0%
0.08 10
 
1.0%
1.13 10
 
1.0%
0.40 10
 
1.0%
Other values (231) 874
89.0%
2023-07-19T17:24:33.152323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 982
19.6%
0 840
16.8%
646
12.9%
1 523
10.5%
- 426
8.5%
2 266
 
5.3%
4 226
 
4.5%
3 218
 
4.4%
5 192
 
3.8%
8 178
 
3.6%
Other values (3) 503
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2946
58.9%
Other Punctuation 982
 
19.6%
Space Separator 646
 
12.9%
Dash Punctuation 426
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 840
28.5%
1 523
17.8%
2 266
 
9.0%
4 226
 
7.7%
3 218
 
7.4%
5 192
 
6.5%
8 178
 
6.0%
7 172
 
5.8%
9 168
 
5.7%
6 163
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 982
100.0%
Space Separator
ValueCountFrequency (%)
646
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 426
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 982
19.6%
0 840
16.8%
646
12.9%
1 523
10.5%
- 426
8.5%
2 266
 
5.3%
4 226
 
4.5%
3 218
 
4.4%
5 192
 
3.8%
8 178
 
3.6%
Other values (3) 503
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 982
19.6%
0 840
16.8%
646
12.9%
1 523
10.5%
- 426
8.5%
2 266
 
5.3%
4 226
 
4.5%
3 218
 
4.4%
5 192
 
3.8%
8 178
 
3.6%
Other values (3) 503
10.1%

1
Real number (ℝ)

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean501.83
Minimum2
Maximum1002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:33.234626image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile51.95
Q1251.75
median501.5
Q3752.25
95-th percentile952.05
Maximum1002
Range1000
Interquartile range (IQR)500.5

Descriptive statistics

Standard deviation289.20271
Coefficient of variation (CV)0.57629618
Kurtosis-1.2006742
Mean501.83
Median Absolute Deviation (MAD)250.5
Skewness0.0015632785
Sum501830
Variance83638.209
MonotonicityNot monotonic
2023-07-19T17:24:33.293046image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1
 
0.1%
674 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
663 1
 
0.1%
662 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
667 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
11 1
0.1%
ValueCountFrequency (%)
1002 1
0.1%
1001 1
0.1%
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%
995 1
0.1%
994 1
0.1%
993 1
0.1%

9.643
Text

Distinct872
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:33.548830image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique784 ?
Unique (%)78.4%

Sample

1st row10.519
2nd row 6.576
3rd row 8.471
4th row 9.693
5th row
ValueCountFrequency (%)
10.214 4
 
0.4%
9.693 3
 
0.3%
8.186 3
 
0.3%
9.211 3
 
0.3%
9.086 3
 
0.3%
8.613 3
 
0.3%
9.474 3
 
0.3%
9.331 2
 
0.2%
10.502 2
 
0.2%
7.869 2
 
0.2%
Other values (861) 938
97.1%
2023-07-19T17:24:33.874123image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 966
16.1%
884
14.7%
1 613
10.2%
9 582
9.7%
8 515
8.6%
0 507
8.5%
6 367
 
6.1%
7 361
 
6.0%
4 323
 
5.4%
5 299
 
5.0%
Other values (2) 583
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4150
69.2%
Other Punctuation 966
 
16.1%
Space Separator 884
 
14.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 613
14.8%
9 582
14.0%
8 515
12.4%
0 507
12.2%
6 367
8.8%
7 361
8.7%
4 323
7.8%
5 299
7.2%
2 292
7.0%
3 291
7.0%
Other Punctuation
ValueCountFrequency (%)
. 966
100.0%
Space Separator
ValueCountFrequency (%)
884
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 966
16.1%
884
14.7%
1 613
10.2%
9 582
9.7%
8 515
8.6%
0 507
8.5%
6 367
 
6.1%
7 361
 
6.0%
4 323
 
5.4%
5 299
 
5.0%
Other values (2) 583
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 966
16.1%
884
14.7%
1 613
10.2%
9 582
9.7%
8 515
8.6%
0 507
8.5%
6 367
 
6.1%
7 361
 
6.0%
4 323
 
5.4%
5 299
 
5.0%
Other values (2) 583
9.7%

0.020
Text

Distinct93
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:34.021483image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)3.3%

Sample

1st row0.033
2nd row0.004
3rd row0.007
4th row0.014
5th row
ValueCountFrequency (%)
0.011 56
 
5.8%
0.009 52
 
5.4%
0.008 46
 
4.8%
0.016 45
 
4.7%
0.010 42
 
4.3%
0.012 41
 
4.2%
0.013 40
 
4.1%
0.007 37
 
3.8%
0.015 33
 
3.4%
0.017 32
 
3.3%
Other values (82) 542
56.1%
2023-07-19T17:24:34.202859image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2258
45.2%
. 966
19.3%
1 492
 
9.8%
2 273
 
5.5%
3 186
 
3.7%
170
 
3.4%
4 125
 
2.5%
5 111
 
2.2%
8 107
 
2.1%
9 104
 
2.1%
Other values (2) 208
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3864
77.3%
Other Punctuation 966
 
19.3%
Space Separator 170
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2258
58.4%
1 492
 
12.7%
2 273
 
7.1%
3 186
 
4.8%
4 125
 
3.2%
5 111
 
2.9%
8 107
 
2.8%
9 104
 
2.7%
6 104
 
2.7%
7 104
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 966
100.0%
Space Separator
ValueCountFrequency (%)
170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2258
45.2%
. 966
19.3%
1 492
 
9.8%
2 273
 
5.5%
3 186
 
3.7%
170
 
3.4%
4 125
 
2.5%
5 111
 
2.2%
8 107
 
2.1%
9 104
 
2.1%
Other values (2) 208
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2258
45.2%
. 966
19.3%
1 492
 
9.8%
2 273
 
5.5%
3 186
 
3.7%
170
 
3.4%
4 125
 
2.5%
5 111
 
2.2%
8 107
 
2.1%
9 104
 
2.1%
Other values (2) 208
 
4.2%

9.130
Text

Distinct855
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:34.465875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique752 ?
Unique (%)75.2%

Sample

1st row 9.378
2nd row 6.621
3rd row 8.092
4th row 8.656
5th row
ValueCountFrequency (%)
7.851 3
 
0.3%
8.576 3
 
0.3%
8.746 3
 
0.3%
8.597 3
 
0.3%
8.269 3
 
0.3%
9.006 3
 
0.3%
8.630 3
 
0.3%
9.151 3
 
0.3%
8.200 3
 
0.3%
7.954 3
 
0.3%
Other values (844) 936
96.9%
2023-07-19T17:24:34.782086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1104
18.4%
. 966
16.1%
8 630
10.5%
9 542
9.0%
7 509
8.5%
1 391
 
6.5%
0 383
 
6.4%
6 359
 
6.0%
2 289
 
4.8%
5 288
 
4.8%
Other values (2) 539
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3930
65.5%
Space Separator 1104
 
18.4%
Other Punctuation 966
 
16.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 630
16.0%
9 542
13.8%
7 509
13.0%
1 391
9.9%
0 383
9.7%
6 359
9.1%
2 289
7.4%
5 288
7.3%
3 277
7.0%
4 262
6.7%
Space Separator
ValueCountFrequency (%)
1104
100.0%
Other Punctuation
ValueCountFrequency (%)
. 966
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1104
18.4%
. 966
16.1%
8 630
10.5%
9 542
9.0%
7 509
8.5%
1 391
 
6.5%
0 383
 
6.4%
6 359
 
6.0%
2 289
 
4.8%
5 288
 
4.8%
Other values (2) 539
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1104
18.4%
. 966
16.1%
8 630
10.5%
9 542
9.0%
7 509
8.5%
1 391
 
6.5%
0 383
 
6.4%
6 359
 
6.0%
2 289
 
4.8%
5 288
 
4.8%
Other values (2) 539
9.0%

0.019
Text

Distinct70
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:34.920949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)2.3%

Sample

1st row0.021
2nd row0.005
3rd row0.007
4th row0.010
5th row
ValueCountFrequency (%)
0.010 75
 
7.8%
0.008 63
 
6.5%
0.011 60
 
6.2%
0.009 57
 
5.9%
0.014 56
 
5.8%
0.007 53
 
5.5%
0.012 50
 
5.2%
0.013 49
 
5.1%
0.006 45
 
4.7%
0.005 38
 
3.9%
Other values (59) 420
43.5%
2023-07-19T17:24:35.096338image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2369
47.4%
. 966
19.3%
1 531
 
10.6%
2 199
 
4.0%
170
 
3.4%
3 135
 
2.7%
4 127
 
2.5%
8 109
 
2.2%
6 108
 
2.2%
5 99
 
2.0%
Other values (2) 187
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3864
77.3%
Other Punctuation 966
 
19.3%
Space Separator 170
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2369
61.3%
1 531
 
13.7%
2 199
 
5.2%
3 135
 
3.5%
4 127
 
3.3%
8 109
 
2.8%
6 108
 
2.8%
5 99
 
2.6%
7 98
 
2.5%
9 89
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 966
100.0%
Space Separator
ValueCountFrequency (%)
170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2369
47.4%
. 966
19.3%
1 531
 
10.6%
2 199
 
4.0%
170
 
3.4%
3 135
 
2.7%
4 127
 
2.5%
8 109
 
2.2%
6 108
 
2.2%
5 99
 
2.0%
Other values (2) 187
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2369
47.4%
. 966
19.3%
1 531
 
10.6%
2 199
 
4.0%
170
 
3.4%
3 135
 
2.7%
4 127
 
2.5%
8 109
 
2.2%
6 108
 
2.2%
5 99
 
2.0%
Other values (2) 187
 
3.7%

.3
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
888 
*
 
73
A
 
34
B
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters4
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
888
88.8%
* 73
 
7.3%
A 34
 
3.4%
B 5
 
0.5%

Length

2023-07-19T17:24:35.164739image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:35.210247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
73
65.2%
a 34
30.4%
b 5
 
4.5%

Most occurring characters

ValueCountFrequency (%)
888
88.8%
* 73
 
7.3%
A 34
 
3.4%
B 5
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 888
88.8%
Other Punctuation 73
 
7.3%
Uppercase Letter 39
 
3.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 34
87.2%
B 5
 
12.8%
Space Separator
ValueCountFrequency (%)
888
100.0%
Other Punctuation
ValueCountFrequency (%)
* 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 961
96.1%
Latin 39
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
888
92.4%
* 73
 
7.6%
Latin
ValueCountFrequency (%)
A 34
87.2%
B 5
 
12.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
888
88.8%
* 73
 
7.3%
A 34
 
3.4%
B 5
 
0.5%

0.482
Text

Distinct687
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:35.434196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique465 ?
Unique (%)46.5%

Sample

1st row 0.999
2nd row-0.019
3rd row 0.370
4th row 0.902
5th row 1.336
ValueCountFrequency (%)
0.456 5
 
0.5%
0.570 5
 
0.5%
1.125 5
 
0.5%
0.473 5
 
0.5%
0.595 4
 
0.4%
0.510 4
 
0.4%
1.260 4
 
0.4%
0.644 4
 
0.4%
1.500 4
 
0.4%
1.113 4
 
0.4%
Other values (666) 944
95.5%
2023-07-19T17:24:35.741268image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1118
18.6%
1027
17.1%
. 988
16.5%
1 643
10.7%
4 348
 
5.8%
5 343
 
5.7%
6 295
 
4.9%
3 283
 
4.7%
9 260
 
4.3%
2 253
 
4.2%
Other values (3) 442
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3952
65.9%
Space Separator 1027
 
17.1%
Other Punctuation 988
 
16.5%
Dash Punctuation 33
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1118
28.3%
1 643
16.3%
4 348
 
8.8%
5 343
 
8.7%
6 295
 
7.5%
3 283
 
7.2%
9 260
 
6.6%
2 253
 
6.4%
7 215
 
5.4%
8 194
 
4.9%
Space Separator
ValueCountFrequency (%)
1027
100.0%
Other Punctuation
ValueCountFrequency (%)
. 988
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1118
18.6%
1027
17.1%
. 988
16.5%
1 643
10.7%
4 348
 
5.8%
5 343
 
5.7%
6 295
 
4.9%
3 283
 
4.7%
9 260
 
4.3%
2 253
 
4.2%
Other values (3) 442
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1118
18.6%
1027
17.1%
. 988
16.5%
1 643
10.7%
4 348
 
5.8%
5 343
 
5.7%
6 295
 
4.9%
3 283
 
4.7%
9 260
 
4.3%
2 253
 
4.2%
Other values (3) 442
 
7.4%

0.025
Text

Distinct81
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:35.879639image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)2.1%

Sample

1st row0.002
2nd row0.004
3rd row0.009
4th row0.013
5th row0.020
ValueCountFrequency (%)
0.015 170
 
17.2%
0.020 61
 
6.2%
0.010 36
 
3.6%
0.009 34
 
3.4%
0.003 32
 
3.2%
0.012 31
 
3.1%
0.011 30
 
3.0%
0.007 30
 
3.0%
0.016 30
 
3.0%
0.014 30
 
3.0%
Other values (70) 504
51.0%
2023-07-19T17:24:36.052173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2313
46.3%
. 988
19.8%
1 523
 
10.5%
2 290
 
5.8%
5 241
 
4.8%
3 136
 
2.7%
4 119
 
2.4%
7 94
 
1.9%
9 88
 
1.8%
6 83
 
1.7%
Other values (2) 125
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3952
79.0%
Other Punctuation 988
 
19.8%
Space Separator 60
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2313
58.5%
1 523
 
13.2%
2 290
 
7.3%
5 241
 
6.1%
3 136
 
3.4%
4 119
 
3.0%
7 94
 
2.4%
9 88
 
2.2%
6 83
 
2.1%
8 65
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 988
100.0%
Space Separator
ValueCountFrequency (%)
60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2313
46.3%
. 988
19.8%
1 523
 
10.5%
2 290
 
5.8%
5 241
 
4.8%
3 136
 
2.7%
4 119
 
2.4%
7 94
 
1.9%
9 88
 
1.8%
6 83
 
1.7%
Other values (2) 125
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2313
46.3%
. 988
19.8%
1 523
 
10.5%
2 290
 
5.8%
5 241
 
4.8%
3 136
 
2.7%
4 119
 
2.4%
7 94
 
1.9%
9 88
 
1.8%
6 83
 
1.7%
Other values (2) 125
 
2.5%

T
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
T
607 
G
381 
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters3
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowG
2nd rowG
3rd rowT
4th rowT
5th rowG

Common Values

ValueCountFrequency (%)
T 607
60.7%
G 381
38.1%
12
 
1.2%

Length

2023-07-19T17:24:36.225063image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:36.270335image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
t 607
61.4%
g 381
38.6%

Most occurring characters

ValueCountFrequency (%)
T 607
60.7%
G 381
38.1%
12
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 988
98.8%
Space Separator 12
 
1.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 607
61.4%
G 381
38.6%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 988
98.8%
Common 12
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 607
61.4%
G 381
38.6%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 607
60.7%
G 381
38.1%
12
 
1.2%

0.55
Text

Distinct215
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:36.453475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)7.0%

Sample

1st row1.04
2nd row0.00
3rd row0.43
4th row0.90
5th row1.55
ValueCountFrequency (%)
0.58 19
 
1.9%
0.98 17
 
1.7%
1.04 17
 
1.7%
1.01 16
 
1.6%
0.57 16
 
1.6%
0.54 15
 
1.5%
0.60 15
 
1.5%
0.99 14
 
1.4%
0.53 14
 
1.4%
0.97 14
 
1.4%
Other values (204) 831
84.1%
2023-07-19T17:24:36.715831image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 988
24.7%
0 932
23.3%
1 466
11.7%
5 256
 
6.4%
9 232
 
5.8%
6 214
 
5.3%
4 204
 
5.1%
2 183
 
4.6%
7 164
 
4.1%
8 147
 
3.7%
Other values (3) 214
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2941
73.5%
Other Punctuation 988
 
24.7%
Space Separator 48
 
1.2%
Dash Punctuation 23
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 932
31.7%
1 466
15.8%
5 256
 
8.7%
9 232
 
7.9%
6 214
 
7.3%
4 204
 
6.9%
2 183
 
6.2%
7 164
 
5.6%
8 147
 
5.0%
3 143
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 988
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 988
24.7%
0 932
23.3%
1 466
11.7%
5 256
 
6.4%
9 232
 
5.8%
6 214
 
5.3%
4 204
 
5.1%
2 183
 
4.6%
7 164
 
4.1%
8 147
 
3.7%
Other values (3) 214
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 988
24.7%
0 932
23.3%
1 466
11.7%
5 256
 
6.4%
9 232
 
5.8%
6 214
 
5.3%
4 204
 
5.1%
2 183
 
4.6%
7 164
 
4.1%
8 147
 
3.7%
Other values (3) 214
 
5.3%

0.03
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
0.01
378 
0.02
301 
0.03
106 
0.00
87 
0.04
 
34
Other values (21)
94 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.0%

Sample

1st row0.00
2nd row0.00
3rd row0.01
4th row0.01
5th row0.03

Common Values

ValueCountFrequency (%)
0.01 378
37.8%
0.02 301
30.1%
0.03 106
 
10.6%
0.00 87
 
8.7%
0.04 34
 
3.4%
0.05 26
 
2.6%
12
 
1.2%
0.07 9
 
0.9%
0.06 9
 
0.9%
0.09 9
 
0.9%
Other values (16) 29
 
2.9%

Length

2023-07-19T17:24:36.790721image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.01 378
38.3%
0.02 301
30.5%
0.03 106
 
10.7%
0.00 87
 
8.8%
0.04 34
 
3.4%
0.05 26
 
2.6%
0.07 9
 
0.9%
0.06 9
 
0.9%
0.09 9
 
0.9%
0.17 4
 
0.4%
Other values (15) 25
 
2.5%

Most occurring characters

ValueCountFrequency (%)
0 2043
51.1%
. 988
24.7%
1 397
 
9.9%
2 306
 
7.6%
3 108
 
2.7%
48
 
1.2%
4 36
 
0.9%
5 27
 
0.7%
7 15
 
0.4%
6 14
 
0.4%
Other values (2) 18
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2964
74.1%
Other Punctuation 988
 
24.7%
Space Separator 48
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2043
68.9%
1 397
 
13.4%
2 306
 
10.3%
3 108
 
3.6%
4 36
 
1.2%
5 27
 
0.9%
7 15
 
0.5%
6 14
 
0.5%
9 13
 
0.4%
8 5
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 988
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2043
51.1%
. 988
24.7%
1 397
 
9.9%
2 306
 
7.6%
3 108
 
2.7%
48
 
1.2%
4 36
 
0.9%
5 27
 
0.7%
7 15
 
0.4%
6 14
 
0.4%
Other values (2) 18
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2043
51.1%
. 988
24.7%
1 397
 
9.9%
2 306
 
7.6%
3 108
 
2.7%
48
 
1.2%
4 36
 
0.9%
5 27
 
0.7%
7 15
 
0.4%
6 14
 
0.4%
Other values (2) 18
 
0.4%

L
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct16
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
L
595 
H
264 
I
 
37
A
 
23
O
 
21
Other values (11)
60 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st rowI
2nd rowH
3rd rowL
4th rowL
5th rowI

Common Values

ValueCountFrequency (%)
L 595
59.5%
H 264
26.4%
I 37
 
3.7%
A 23
 
2.3%
O 21
 
2.1%
R 14
 
1.4%
T 12
 
1.2%
E 11
 
1.1%
K 7
 
0.7%
C 5
 
0.5%
Other values (6) 11
 
1.1%

Length

2023-07-19T17:24:36.834274image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
l 595
59.5%
h 264
26.4%
i 37
 
3.7%
a 23
 
2.3%
o 21
 
2.1%
r 14
 
1.4%
t 12
 
1.2%
e 11
 
1.1%
k 7
 
0.7%
c 5
 
0.5%
Other values (6) 11
 
1.1%

Most occurring characters

ValueCountFrequency (%)
L 595
59.5%
H 264
26.4%
I 37
 
3.7%
A 23
 
2.3%
O 21
 
2.1%
R 14
 
1.4%
T 12
 
1.2%
E 11
 
1.1%
K 7
 
0.7%
C 5
 
0.5%
Other values (6) 11
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 595
59.5%
H 264
26.4%
I 37
 
3.7%
A 23
 
2.3%
O 21
 
2.1%
R 14
 
1.4%
T 12
 
1.2%
E 11
 
1.1%
K 7
 
0.7%
C 5
 
0.5%
Other values (6) 11
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 595
59.5%
H 264
26.4%
I 37
 
3.7%
A 23
 
2.3%
O 21
 
2.1%
R 14
 
1.4%
T 12
 
1.2%
E 11
 
1.1%
K 7
 
0.7%
C 5
 
0.5%
Other values (6) 11
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
L 595
59.5%
H 264
26.4%
I 37
 
3.7%
A 23
 
2.3%
O 21
 
2.1%
R 14
 
1.4%
T 12
 
1.2%
E 11
 
1.1%
K 7
 
0.7%
C 5
 
0.5%
Other values (6) 11
 
1.1%

.4
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
902 
*
98 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
902
90.2%
* 98
 
9.8%

Length

2023-07-19T17:24:36.877913image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:36.923142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
98
100.0%

Most occurring characters

ValueCountFrequency (%)
902
90.2%
* 98
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Space Separator 902
90.2%
Other Punctuation 98
 
9.8%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
902
100.0%
Other Punctuation
ValueCountFrequency (%)
* 98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
902
90.2%
* 98
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
902
90.2%
* 98
 
9.8%

9.2043
Real number (ℝ)

HIGH CORRELATION 

Distinct984
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5250448
Minimum2.0371
Maximum12.697
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:36.969354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.0371
5-th percentile6.3321
Q17.815625
median8.6055
Q39.236925
95-th percentile10.58806
Maximum12.697
Range10.6599
Interquartile range (IQR)1.4213

Descriptive statistics

Standard deviation1.2918017
Coefficient of variation (CV)0.1515302
Kurtosis1.6128814
Mean8.5250448
Median Absolute Deviation (MAD)0.72305
Skewness-0.27846075
Sum8525.0448
Variance1.6687517
MonotonicityNot monotonic
2023-07-19T17:24:37.026170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.1836 2
 
0.2%
8.8563 2
 
0.2%
7.0837 2
 
0.2%
8.6045 2
 
0.2%
8.5955 2
 
0.2%
8.4078 2
 
0.2%
8.6374 2
 
0.2%
8.3312 2
 
0.2%
8.9786 2
 
0.2%
8.9812 2
 
0.2%
Other values (974) 980
98.0%
ValueCountFrequency (%)
2.0371 1
0.1%
2.3579 1
0.1%
4.0452 1
0.1%
4.412 1
0.1%
4.5366 1
0.1%
4.7803 1
0.1%
4.9354 1
0.1%
4.9895 1
0.1%
5.0025 1
0.1%
5.0831 1
0.1%
ValueCountFrequency (%)
12.697 1
0.1%
12.4598 1
0.1%
12.4488 1
0.1%
12.2227 1
0.1%
12.2167 1
0.1%
12.1528 1
0.1%
12.126 1
0.1%
12.0119 1
0.1%
11.8733 1
0.1%
11.8607 1
0.1%

0.0020
Real number (ℝ)

HIGH CORRELATION 

Distinct101
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0035566
Minimum0.0003
Maximum0.2283
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:37.081838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.0003
5-th percentile0.0007
Q10.0012
median0.0016
Q30.002325
95-th percentile0.0062
Maximum0.2283
Range0.228
Interquartile range (IQR)0.001125

Descriptive statistics

Standard deviation0.012963667
Coefficient of variation (CV)3.6449605
Kurtosis149.584
Mean0.0035566
Median Absolute Deviation (MAD)0.0005
Skewness11.236393
Sum3.5566
Variance0.00016805665
MonotonicityNot monotonic
2023-07-19T17:24:37.138220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0013 60
 
6.0%
0.0016 60
 
6.0%
0.0015 60
 
6.0%
0.0012 54
 
5.4%
0.0017 49
 
4.9%
0.0014 49
 
4.9%
0.0011 48
 
4.8%
0.001 45
 
4.5%
0.0019 40
 
4.0%
0.0018 39
 
3.9%
Other values (91) 496
49.6%
ValueCountFrequency (%)
0.0003 1
 
0.1%
0.0004 2
 
0.2%
0.0005 10
 
1.0%
0.0006 22
2.2%
0.0007 23
2.3%
0.0008 36
3.6%
0.0009 38
3.8%
0.001 45
4.5%
0.0011 48
4.8%
0.0012 54
5.4%
ValueCountFrequency (%)
0.2283 1
0.1%
0.1671 1
0.1%
0.1504 1
0.1%
0.1217 1
0.1%
0.1212 1
0.1%
0.0993 1
0.1%
0.0831 1
0.1%
0.0614 1
0.1%
0.0535 1
0.1%
0.0494 1
0.1%

0.017
Text

Distinct86
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:37.255865image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)3.8%

Sample

1st row0.015
2nd row0.008
3rd row0.015
4th row0.019
5th row0.091
ValueCountFrequency (%)
0.016 61
 
6.1%
0.014 60
 
6.0%
0.015 60
 
6.0%
0.012 52
 
5.2%
0.017 51
 
5.1%
0.013 47
 
4.7%
0.011 47
 
4.7%
0.009 46
 
4.6%
0.020 45
 
4.5%
0.010 44
 
4.4%
Other values (75) 480
48.3%
2023-07-19T17:24:37.437001image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2218
44.4%
. 993
19.9%
1 614
 
12.3%
2 321
 
6.4%
3 156
 
3.1%
4 126
 
2.5%
5 117
 
2.3%
8 113
 
2.3%
7 104
 
2.1%
6 103
 
2.1%
Other values (2) 135
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3972
79.4%
Other Punctuation 993
 
19.9%
Space Separator 35
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2218
55.8%
1 614
 
15.5%
2 321
 
8.1%
3 156
 
3.9%
4 126
 
3.2%
5 117
 
2.9%
8 113
 
2.8%
7 104
 
2.6%
6 103
 
2.6%
9 100
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 993
100.0%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2218
44.4%
. 993
19.9%
1 614
 
12.3%
2 321
 
6.4%
3 156
 
3.1%
4 126
 
2.5%
5 117
 
2.3%
8 113
 
2.3%
7 104
 
2.1%
6 103
 
2.1%
Other values (2) 135
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2218
44.4%
. 993
19.9%
1 614
 
12.3%
2 321
 
6.4%
3 156
 
3.1%
4 126
 
2.5%
5 117
 
2.3%
8 113
 
2.3%
7 104
 
2.1%
6 103
 
2.1%
Other values (2) 135
 
2.7%

87
Text

Distinct160
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:37.628285image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3000
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)3.0%

Sample

1st row120
2nd row127
3rd row201
4th row161
5th row 87
ValueCountFrequency (%)
131 22
 
2.2%
109 21
 
2.1%
140 17
 
1.7%
130 16
 
1.6%
96 15
 
1.5%
103 15
 
1.5%
126 14
 
1.4%
98 14
 
1.4%
148 14
 
1.4%
119 14
 
1.4%
Other values (149) 831
83.7%
2023-07-19T17:24:37.864214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 972
32.4%
2 252
 
8.4%
9 237
 
7.9%
229
 
7.6%
3 214
 
7.1%
0 211
 
7.0%
4 201
 
6.7%
8 185
 
6.2%
5 174
 
5.8%
6 171
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2771
92.4%
Space Separator 229
 
7.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 972
35.1%
2 252
 
9.1%
9 237
 
8.6%
3 214
 
7.7%
0 211
 
7.6%
4 201
 
7.3%
8 185
 
6.7%
5 174
 
6.3%
6 171
 
6.2%
7 154
 
5.6%
Space Separator
ValueCountFrequency (%)
229
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 972
32.4%
2 252
 
8.4%
9 237
 
7.9%
229
 
7.6%
3 214
 
7.1%
0 211
 
7.0%
4 201
 
6.7%
8 185
 
6.2%
5 174
 
5.8%
6 171
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 972
32.4%
2 252
 
8.4%
9 237
 
7.9%
229
 
7.6%
3 214
 
7.1%
0 211
 
7.0%
4 201
 
6.7%
8 185
 
6.2%
5 174
 
5.8%
6 171
 
5.7%

.5
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
883 
*
97 
A
 
11
B
 
7
-
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters5
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
883
88.3%
* 97
 
9.7%
A 11
 
1.1%
B 7
 
0.7%
- 2
 
0.2%

Length

2023-07-19T17:24:37.936126image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:37.984539image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
99
84.6%
a 11
 
9.4%
b 7
 
6.0%

Most occurring characters

ValueCountFrequency (%)
883
88.3%
* 97
 
9.7%
A 11
 
1.1%
B 7
 
0.7%
- 2
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 883
88.3%
Other Punctuation 97
 
9.7%
Uppercase Letter 18
 
1.8%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 11
61.1%
B 7
38.9%
Space Separator
ValueCountFrequency (%)
883
100.0%
Other Punctuation
ValueCountFrequency (%)
* 97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 982
98.2%
Latin 18
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
883
89.9%
* 97
 
9.9%
- 2
 
0.2%
Latin
ValueCountFrequency (%)
A 11
61.1%
B 7
38.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
883
88.3%
* 97
 
9.7%
A 11
 
1.1%
B 7
 
0.7%
- 2
 
0.2%

9.17
Text

Distinct426
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:38.182878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique195 ?
Unique (%)19.5%

Sample

1st row 9.37
2nd row 6.60
3rd row 8.12
4th row 8.68
5th row12.30
ValueCountFrequency (%)
8.33 10
 
1.0%
8.66 10
 
1.0%
7.85 9
 
0.9%
9.07 9
 
0.9%
8.30 8
 
0.8%
7.74 8
 
0.8%
8.95 8
 
0.8%
8.68 8
 
0.8%
8.22 7
 
0.7%
8.07 7
 
0.7%
Other values (415) 909
91.5%
2023-07-19T17:24:38.456910image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 993
19.9%
941
18.8%
8 546
10.9%
9 432
8.6%
7 415
8.3%
1 298
 
6.0%
6 275
 
5.5%
0 267
 
5.3%
5 227
 
4.5%
3 221
 
4.4%
Other values (2) 385
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3066
61.3%
Other Punctuation 993
 
19.9%
Space Separator 941
 
18.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 546
17.8%
9 432
14.1%
7 415
13.5%
1 298
9.7%
6 275
9.0%
0 267
8.7%
5 227
7.4%
3 221
7.2%
4 196
 
6.4%
2 189
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 993
100.0%
Space Separator
ValueCountFrequency (%)
941
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 993
19.9%
941
18.8%
8 546
10.9%
9 432
8.6%
7 415
8.3%
1 298
 
6.0%
6 275
 
5.5%
0 267
 
5.3%
5 227
 
4.5%
3 221
 
4.4%
Other values (2) 385
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 993
19.9%
941
18.8%
8 546
10.9%
9 432
8.6%
7 415
8.3%
1 298
 
6.0%
6 275
 
5.5%
0 267
 
5.3%
5 227
 
4.5%
3 221
 
4.4%
Other values (2) 385
 
7.7%

9.24
Text

Distinct424
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:38.683712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique168 ?
Unique (%)16.8%

Sample

1st row 9.44
2nd row 6.62
3rd row 8.18
4th row 8.74
5th row12.60
ValueCountFrequency (%)
8.35 9
 
0.9%
8.73 8
 
0.8%
8.61 8
 
0.8%
8.76 8
 
0.8%
8.56 7
 
0.7%
8.75 7
 
0.7%
7.77 7
 
0.7%
9.07 7
 
0.7%
9.15 7
 
0.7%
8.40 7
 
0.7%
Other values (413) 918
92.4%
2023-07-19T17:24:38.953861image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 993
19.9%
918
18.4%
8 536
10.7%
9 443
8.9%
7 433
8.7%
1 325
 
6.5%
0 289
 
5.8%
6 263
 
5.3%
5 222
 
4.4%
4 202
 
4.0%
Other values (2) 376
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3089
61.8%
Other Punctuation 993
 
19.9%
Space Separator 918
 
18.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 536
17.4%
9 443
14.3%
7 433
14.0%
1 325
10.5%
0 289
9.4%
6 263
8.5%
5 222
7.2%
4 202
 
6.5%
3 196
 
6.3%
2 180
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 993
100.0%
Space Separator
ValueCountFrequency (%)
918
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 993
19.9%
918
18.4%
8 536
10.7%
9 443
8.9%
7 433
8.7%
1 325
 
6.5%
0 289
 
5.8%
6 263
 
5.3%
5 222
 
4.4%
4 202
 
4.0%
Other values (2) 376
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 993
19.9%
918
18.4%
8 536
10.7%
9 443
8.9%
7 433
8.7%
1 325
 
6.5%
0 289
 
5.8%
6 263
 
5.3%
5 222
 
4.4%
4 202
 
4.0%
Other values (2) 376
 
7.5%


Categorical

HIGH CORRELATION  IMBALANCE 

Distinct22
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
978 
0.17
 
2
3.74
 
1
0.49
 
1
2.09
 
1
Other values (17)
 
17

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)2.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
978
97.8%
0.17 2
 
0.2%
3.74 1
 
0.1%
0.49 1
 
0.1%
2.09 1
 
0.1%
0.61 1
 
0.1%
315.80 1
 
0.1%
9.16 1
 
0.1%
146.80 1
 
0.1%
0.93 1
 
0.1%
Other values (12) 12
 
1.2%

Length

2023-07-19T17:24:39.030127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.17 2
 
9.1%
356.00 1
 
4.5%
366.00 1
 
4.5%
0.81 1
 
4.5%
37.82 1
 
4.5%
9.06 1
 
4.5%
2.64 1
 
4.5%
3.65 1
 
4.5%
138.66 1
 
4.5%
0.10 1
 
4.5%
Other values (11) 11
50.0%

Most occurring characters

ValueCountFrequency (%)
6897
98.5%
. 22
 
0.3%
0 17
 
0.2%
3 11
 
0.2%
6 11
 
0.2%
1 10
 
0.1%
4 7
 
0.1%
8 6
 
0.1%
7 5
 
0.1%
9 5
 
0.1%
Other values (2) 9
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 6897
98.5%
Decimal Number 81
 
1.2%
Other Punctuation 22
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
21.0%
3 11
13.6%
6 11
13.6%
1 10
12.3%
4 7
8.6%
8 6
 
7.4%
7 5
 
6.2%
9 5
 
6.2%
5 5
 
6.2%
2 4
 
4.9%
Space Separator
ValueCountFrequency (%)
6897
100.0%
Other Punctuation
ValueCountFrequency (%)
. 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6897
98.5%
. 22
 
0.3%
0 17
 
0.2%
3 11
 
0.2%
6 11
 
0.2%
1 10
 
0.1%
4 7
 
0.1%
8 6
 
0.1%
7 5
 
0.1%
9 5
 
0.1%
Other values (2) 9
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6897
98.5%
. 22
 
0.3%
0 17
 
0.2%
3 11
 
0.2%
6 11
 
0.2%
1 10
 
0.1%
4 7
 
0.1%
8 6
 
0.1%
7 5
 
0.1%
9 5
 
0.1%
Other values (2) 9
 
0.1%

.6
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
419 
C
375 
D
98 
U
68 
P
 
24
Other values (2)
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters7
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowC
2nd rowC
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
419
41.9%
C 375
37.5%
D 98
 
9.8%
U 68
 
6.8%
P 24
 
2.4%
R 12
 
1.2%
M 4
 
0.4%

Length

2023-07-19T17:24:39.073135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:39.124511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
c 375
64.5%
d 98
 
16.9%
u 68
 
11.7%
p 24
 
4.1%
r 12
 
2.1%
m 4
 
0.7%

Most occurring characters

ValueCountFrequency (%)
419
41.9%
C 375
37.5%
D 98
 
9.8%
U 68
 
6.8%
P 24
 
2.4%
R 12
 
1.2%
M 4
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 581
58.1%
Space Separator 419
41.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 375
64.5%
D 98
 
16.9%
U 68
 
11.7%
P 24
 
4.1%
R 12
 
2.1%
M 4
 
0.7%
Space Separator
ValueCountFrequency (%)
419
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 581
58.1%
Common 419
41.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 375
64.5%
D 98
 
16.9%
U 68
 
11.7%
P 24
 
4.1%
R 12
 
2.1%
M 4
 
0.7%
Common
ValueCountFrequency (%)
419
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
419
41.9%
C 375
37.5%
D 98
 
9.8%
U 68
 
6.8%
P 24
 
2.4%
R 12
 
1.2%
M 4
 
0.4%

.7
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
931 
2
 
45
1
 
24

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
931
93.1%
2 45
 
4.5%
1 24
 
2.4%

Length

2023-07-19T17:24:39.170556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:39.214402image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 45
65.2%
1 24
34.8%

Most occurring characters

ValueCountFrequency (%)
931
93.1%
2 45
 
4.5%
1 24
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 931
93.1%
Decimal Number 69
 
6.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 45
65.2%
1 24
34.8%
Space Separator
ValueCountFrequency (%)
931
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
931
93.1%
2 45
 
4.5%
1 24
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
931
93.1%
2 45
 
4.5%
1 24
 
2.4%

.8
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
965 
A
 
20
C
 
10
B
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters4
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
965
96.5%
A 20
 
2.0%
C 10
 
1.0%
B 5
 
0.5%

Length

2023-07-19T17:24:39.253556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:39.299589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
a 20
57.1%
c 10
28.6%
b 5
 
14.3%

Most occurring characters

ValueCountFrequency (%)
965
96.5%
A 20
 
2.0%
C 10
 
1.0%
B 5
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 965
96.5%
Uppercase Letter 35
 
3.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 20
57.1%
C 10
28.6%
B 5
 
14.3%
Space Separator
ValueCountFrequency (%)
965
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 965
96.5%
Latin 35
 
3.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 20
57.1%
C 10
28.6%
B 5
 
14.3%
Common
ValueCountFrequency (%)
965
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
965
96.5%
A 20
 
2.0%
C 10
 
1.0%
B 5
 
0.5%


Text

Distinct154
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:39.543918image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10000
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)13.7%

Sample

1st row
2nd row00000+3852
3rd row
4th row
5th row
ValueCountFrequency (%)
00021+2706 2
 
1.2%
00042+6217 2
 
1.2%
00008+3647 2
 
1.2%
00069-3036 2
 
1.2%
00024+1047 2
 
1.2%
00026+6606 2
 
1.2%
00029+7122 2
 
1.2%
00031+0816 2
 
1.2%
00028+8017 2
 
1.2%
00046+3416 2
 
1.2%
Other values (143) 149
88.2%
2023-07-19T17:24:39.862368image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8310
83.1%
0 604
 
6.0%
1 146
 
1.5%
2 123
 
1.2%
3 113
 
1.1%
4 107
 
1.1%
5 107
 
1.1%
+ 106
 
1.1%
6 90
 
0.9%
9 83
 
0.8%
Other values (3) 211
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 8310
83.1%
Decimal Number 1521
 
15.2%
Math Symbol 106
 
1.1%
Dash Punctuation 63
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 604
39.7%
1 146
 
9.6%
2 123
 
8.1%
3 113
 
7.4%
4 107
 
7.0%
5 107
 
7.0%
6 90
 
5.9%
9 83
 
5.5%
7 78
 
5.1%
8 70
 
4.6%
Space Separator
ValueCountFrequency (%)
8310
100.0%
Math Symbol
ValueCountFrequency (%)
+ 106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8310
83.1%
0 604
 
6.0%
1 146
 
1.5%
2 123
 
1.2%
3 113
 
1.1%
4 107
 
1.1%
5 107
 
1.1%
+ 106
 
1.1%
6 90
 
0.9%
9 83
 
0.8%
Other values (3) 211
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8310
83.1%
0 604
 
6.0%
1 146
 
1.5%
2 123
 
1.2%
3 113
 
1.1%
4 107
 
1.1%
5 107
 
1.1%
+ 106
 
1.1%
6 90
 
0.9%
9 83
 
0.8%
Other values (3) 211
 
2.1%

.9
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
831 
I
142 
H
 
25
M
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters4
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd rowI
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
831
83.1%
I 142
 
14.2%
H 25
 
2.5%
M 2
 
0.2%

Length

2023-07-19T17:24:39.940000image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:39.986145image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
i 142
84.0%
h 25
 
14.8%
m 2
 
1.2%

Most occurring characters

ValueCountFrequency (%)
831
83.1%
I 142
 
14.2%
H 25
 
2.5%
M 2
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 831
83.1%
Uppercase Letter 169
 
16.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 142
84.0%
H 25
 
14.8%
M 2
 
1.2%
Space Separator
ValueCountFrequency (%)
831
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 831
83.1%
Latin 169
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 142
84.0%
H 25
 
14.8%
M 2
 
1.2%
Common
ValueCountFrequency (%)
831
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
831
83.1%
I 142
 
14.2%
H 25
 
2.5%
M 2
 
0.2%


Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
831 
1
137 
2
 
32

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row 1
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
831
83.1%
1 137
 
13.7%
2 32
 
3.2%

Length

2023-07-19T17:24:40.028126image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:40.072650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 137
81.1%
2 32
 
18.9%

Most occurring characters

ValueCountFrequency (%)
1831
91.5%
1 137
 
6.9%
2 32
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 1831
91.5%
Decimal Number 169
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 137
81.1%
2 32
 
18.9%
Space Separator
ValueCountFrequency (%)
1831
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1831
91.5%
1 137
 
6.9%
2 32
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1831
91.5%
1 137
 
6.9%
2 32
 
1.6%

1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
1
897 
2
102 
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row 1
2nd row 1
3rd row 1
4th row 1
5th row 1

Common Values

ValueCountFrequency (%)
1 897
89.7%
2 102
 
10.2%
1
 
0.1%

Length

2023-07-19T17:24:40.112603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:40.156492image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 897
89.8%
2 102
 
10.2%

Most occurring characters

ValueCountFrequency (%)
1001
50.0%
1 897
44.9%
2 102
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 1001
50.0%
Decimal Number 999
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 897
89.8%
2 102
 
10.2%
Space Separator
ValueCountFrequency (%)
1001
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1001
50.0%
1 897
44.9%
2 102
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1001
50.0%
1 897
44.9%
2 102
 
5.1%

.10
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
840 
C
117 
G
 
20
X
 
17
O
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters6
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
840
84.0%
C 117
 
11.7%
G 20
 
2.0%
X 17
 
1.7%
O 4
 
0.4%
V 2
 
0.2%

Length

2023-07-19T17:24:40.199100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:40.248200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
c 117
73.1%
g 20
 
12.5%
x 17
 
10.6%
o 4
 
2.5%
v 2
 
1.2%

Most occurring characters

ValueCountFrequency (%)
840
84.0%
C 117
 
11.7%
G 20
 
2.0%
X 17
 
1.7%
O 4
 
0.4%
V 2
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 840
84.0%
Uppercase Letter 160
 
16.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 117
73.1%
G 20
 
12.5%
X 17
 
10.6%
O 4
 
2.5%
V 2
 
1.2%
Space Separator
ValueCountFrequency (%)
840
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 840
84.0%
Latin 160
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 117
73.1%
G 20
 
12.5%
X 17
 
10.6%
O 4
 
2.5%
V 2
 
1.2%
Common
ValueCountFrequency (%)
840
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
840
84.0%
C 117
 
11.7%
G 20
 
2.0%
X 17
 
1.7%
O 4
 
0.4%
V 2
 
0.2%

.11
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
970 
S
 
14
P
 
8
I
 
6
L
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters6
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
970
97.0%
S 14
 
1.4%
P 8
 
0.8%
I 6
 
0.6%
L 1
 
0.1%
F 1
 
0.1%

Length

2023-07-19T17:24:40.291340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:40.340373image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
s 14
46.7%
p 8
26.7%
i 6
20.0%
l 1
 
3.3%
f 1
 
3.3%

Most occurring characters

ValueCountFrequency (%)
970
97.0%
S 14
 
1.4%
P 8
 
0.8%
I 6
 
0.6%
L 1
 
0.1%
F 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 970
97.0%
Uppercase Letter 30
 
3.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 14
46.7%
P 8
26.7%
I 6
20.0%
L 1
 
3.3%
F 1
 
3.3%
Space Separator
ValueCountFrequency (%)
970
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 970
97.0%
Latin 30
 
3.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 14
46.7%
P 8
26.7%
I 6
20.0%
L 1
 
3.3%
F 1
 
3.3%
Common
ValueCountFrequency (%)
970
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
970
97.0%
S 14
 
1.4%
P 8
 
0.8%
I 6
 
0.6%
L 1
 
0.1%
F 1
 
0.1%

.12
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
825 
A
86 
S
 
58
B
 
13
D
 
13

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters6
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
825
82.5%
A 86
 
8.6%
S 58
 
5.8%
B 13
 
1.3%
D 13
 
1.3%
C 5
 
0.5%

Length

2023-07-19T17:24:40.382763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:40.432094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
a 86
49.1%
s 58
33.1%
b 13
 
7.4%
d 13
 
7.4%
c 5
 
2.9%

Most occurring characters

ValueCountFrequency (%)
825
82.5%
A 86
 
8.6%
S 58
 
5.8%
B 13
 
1.3%
D 13
 
1.3%
C 5
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 825
82.5%
Uppercase Letter 175
 
17.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 86
49.1%
S 58
33.1%
B 13
 
7.4%
D 13
 
7.4%
C 5
 
2.9%
Space Separator
ValueCountFrequency (%)
825
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 825
82.5%
Latin 175
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 86
49.1%
S 58
33.1%
B 13
 
7.4%
D 13
 
7.4%
C 5
 
2.9%
Common
ValueCountFrequency (%)
825
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
825
82.5%
A 86
 
8.6%
S 58
 
5.8%
B 13
 
1.3%
D 13
 
1.3%
C 5
 
0.5%

.1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
898 
AB
96 
BA
 
3
AS
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters4
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
898
89.8%
AB 96
 
9.6%
BA 3
 
0.3%
AS 3
 
0.3%

Length

2023-07-19T17:24:40.476238image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:40.522874image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
ab 96
94.1%
ba 3
 
2.9%
as 3
 
2.9%

Most occurring characters

ValueCountFrequency (%)
1796
89.8%
A 102
 
5.1%
B 99
 
5.0%
S 3
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 1796
89.8%
Uppercase Letter 204
 
10.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 102
50.0%
B 99
48.5%
S 3
 
1.5%
Space Separator
ValueCountFrequency (%)
1796
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1796
89.8%
Latin 204
 
10.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 102
50.0%
B 99
48.5%
S 3
 
1.5%
Common
ValueCountFrequency (%)
1796
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1796
89.8%
A 102
 
5.1%
B 99
 
5.0%
S 3
 
0.1%


Text

Distinct91
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:40.661970image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3000
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)8.0%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
211 3
 
2.9%
169 3
 
2.9%
165 2
 
2.0%
135 2
 
2.0%
91 2
 
2.0%
274 2
 
2.0%
126 2
 
2.0%
261 2
 
2.0%
84 2
 
2.0%
176 2
 
2.0%
Other values (80) 80
78.4%
2023-07-19T17:24:40.876953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2717
90.6%
2 55
 
1.8%
1 53
 
1.8%
3 38
 
1.3%
6 24
 
0.8%
8 23
 
0.8%
9 22
 
0.7%
4 20
 
0.7%
5 19
 
0.6%
7 18
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 2717
90.6%
Decimal Number 283
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 55
19.4%
1 53
18.7%
3 38
13.4%
6 24
8.5%
8 23
8.1%
9 22
 
7.8%
4 20
 
7.1%
5 19
 
6.7%
7 18
 
6.4%
0 11
 
3.9%
Space Separator
ValueCountFrequency (%)
2717
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2717
90.6%
2 55
 
1.8%
1 53
 
1.8%
3 38
 
1.3%
6 24
 
0.8%
8 23
 
0.8%
9 22
 
0.7%
4 20
 
0.7%
5 19
 
0.6%
7 18
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2717
90.6%
2 55
 
1.8%
1 53
 
1.8%
3 38
 
1.3%
6 24
 
0.8%
8 23
 
0.8%
9 22
 
0.7%
4 20
 
0.7%
5 19
 
0.6%
7 18
 
0.6%

.1
Text

Distinct101
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:41.076063image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)9.8%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
0.258 2
 
2.0%
0.142 2
 
2.0%
0.270 1
 
1.0%
0.233 1
 
1.0%
8.198 1
 
1.0%
2.829 1
 
1.0%
1.699 1
 
1.0%
3.809 1
 
1.0%
11.799 1
 
1.0%
1.197 1
 
1.0%
Other values (90) 90
88.2%
2023-07-19T17:24:41.319478image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6486
92.7%
. 102
 
1.5%
0 79
 
1.1%
1 55
 
0.8%
2 45
 
0.6%
5 38
 
0.5%
3 38
 
0.5%
7 37
 
0.5%
4 31
 
0.4%
9 30
 
0.4%
Other values (2) 59
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Space Separator 6486
92.7%
Decimal Number 412
 
5.9%
Other Punctuation 102
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 79
19.2%
1 55
13.3%
2 45
10.9%
5 38
9.2%
3 38
9.2%
7 37
9.0%
4 31
 
7.5%
9 30
 
7.3%
6 30
 
7.3%
8 29
 
7.0%
Space Separator
ValueCountFrequency (%)
6486
100.0%
Other Punctuation
ValueCountFrequency (%)
. 102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6486
92.7%
. 102
 
1.5%
0 79
 
1.1%
1 55
 
0.8%
2 45
 
0.6%
5 38
 
0.5%
3 38
 
0.5%
7 37
 
0.5%
4 31
 
0.4%
9 30
 
0.4%
Other values (2) 59
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6486
92.7%
. 102
 
1.5%
0 79
 
1.1%
1 55
 
0.8%
2 45
 
0.6%
5 38
 
0.5%
3 38
 
0.5%
7 37
 
0.5%
4 31
 
0.4%
9 30
 
0.4%
Other values (2) 59
 
0.8%


Categorical

HIGH CORRELATION  IMBALANCE 

Distinct40
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
898 
0.004
 
8
0.009
 
7
0.005
 
7
0.006
 
5
Other values (35)
 
75

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)1.7%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
898
89.8%
0.004 8
 
0.8%
0.009 7
 
0.7%
0.005 7
 
0.7%
0.006 5
 
0.5%
0.002 5
 
0.5%
0.007 5
 
0.5%
0.013 5
 
0.5%
0.008 4
 
0.4%
0.030 4
 
0.4%
Other values (30) 52
 
5.2%

Length

2023-07-19T17:24:41.395338image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.004 8
 
7.8%
0.005 7
 
6.9%
0.009 7
 
6.9%
0.006 5
 
4.9%
0.002 5
 
4.9%
0.007 5
 
4.9%
0.013 5
 
4.9%
0.030 4
 
3.9%
0.014 4
 
3.9%
0.008 4
 
3.9%
Other values (29) 48
47.1%

Most occurring characters

ValueCountFrequency (%)
4490
89.8%
0 258
 
5.2%
. 102
 
2.0%
1 31
 
0.6%
2 24
 
0.5%
4 23
 
0.5%
3 17
 
0.3%
5 13
 
0.3%
7 13
 
0.3%
9 10
 
0.2%
Other values (2) 19
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 4490
89.8%
Decimal Number 408
 
8.2%
Other Punctuation 102
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 258
63.2%
1 31
 
7.6%
2 24
 
5.9%
4 23
 
5.6%
3 17
 
4.2%
5 13
 
3.2%
7 13
 
3.2%
9 10
 
2.5%
6 10
 
2.5%
8 9
 
2.2%
Space Separator
ValueCountFrequency (%)
4490
100.0%
Other Punctuation
ValueCountFrequency (%)
. 102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4490
89.8%
0 258
 
5.2%
. 102
 
2.0%
1 31
 
0.6%
2 24
 
0.5%
4 23
 
0.5%
3 17
 
0.3%
5 13
 
0.3%
7 13
 
0.3%
9 10
 
0.2%
Other values (2) 19
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4490
89.8%
0 258
 
5.2%
. 102
 
2.0%
1 31
 
0.6%
2 24
 
0.5%
4 23
 
0.5%
3 17
 
0.3%
5 13
 
0.3%
7 13
 
0.3%
9 10
 
0.2%
Other values (2) 19
 
0.4%

.1
Text

Distinct90
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:41.541265image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)7.7%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
0.06 3
 
2.9%
1.35 2
 
2.0%
0.36 2
 
2.0%
0.64 2
 
2.0%
0.13 2
 
2.0%
2.13 2
 
2.0%
0.17 2
 
2.0%
1.64 2
 
2.0%
2.16 2
 
2.0%
1.32 2
 
2.0%
Other values (79) 81
79.4%
2023-07-19T17:24:41.762241image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4592
91.8%
. 102
 
2.0%
0 51
 
1.0%
2 51
 
1.0%
1 49
 
1.0%
3 43
 
0.9%
6 27
 
0.5%
9 19
 
0.4%
8 18
 
0.4%
5 17
 
0.3%
Other values (2) 31
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 4592
91.8%
Decimal Number 306
 
6.1%
Other Punctuation 102
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 51
16.7%
2 51
16.7%
1 49
16.0%
3 43
14.1%
6 27
8.8%
9 19
 
6.2%
8 18
 
5.9%
5 17
 
5.6%
7 17
 
5.6%
4 14
 
4.6%
Space Separator
ValueCountFrequency (%)
4592
100.0%
Other Punctuation
ValueCountFrequency (%)
. 102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4592
91.8%
. 102
 
2.0%
0 51
 
1.0%
2 51
 
1.0%
1 49
 
1.0%
3 43
 
0.9%
6 27
 
0.5%
9 19
 
0.4%
8 18
 
0.4%
5 17
 
0.3%
Other values (2) 31
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4592
91.8%
. 102
 
2.0%
0 51
 
1.0%
2 51
 
1.0%
1 49
 
1.0%
3 43
 
0.9%
6 27
 
0.5%
9 19
 
0.4%
8 18
 
0.4%
5 17
 
0.3%
Other values (2) 31
 
0.6%


Categorical

HIGH CORRELATION  IMBALANCE 

Distinct38
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
898 
0.02
 
12
0.05
 
11
0.03
 
10
0.01
 
10
Other values (33)
 
59

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)2.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
898
89.8%
0.02 12
 
1.2%
0.05 11
 
1.1%
0.03 10
 
1.0%
0.01 10
 
1.0%
0.04 7
 
0.7%
0.14 7
 
0.7%
0.10 3
 
0.3%
0.12 3
 
0.3%
0.13 3
 
0.3%
Other values (28) 36
 
3.6%

Length

2023-07-19T17:24:41.835518image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.02 12
 
11.8%
0.05 11
 
10.8%
0.03 10
 
9.8%
0.01 10
 
9.8%
0.04 7
 
6.9%
0.14 7
 
6.9%
0.10 3
 
2.9%
0.12 3
 
2.9%
0.13 3
 
2.9%
0.08 2
 
2.0%
Other values (27) 34
33.3%

Most occurring characters

ValueCountFrequency (%)
3592
89.8%
0 162
 
4.0%
. 102
 
2.5%
1 36
 
0.9%
2 25
 
0.6%
4 21
 
0.5%
3 19
 
0.5%
5 18
 
0.4%
8 10
 
0.2%
6 8
 
0.2%
Other values (2) 7
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 3592
89.8%
Decimal Number 306
 
7.6%
Other Punctuation 102
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 162
52.9%
1 36
 
11.8%
2 25
 
8.2%
4 21
 
6.9%
3 19
 
6.2%
5 18
 
5.9%
8 10
 
3.3%
6 8
 
2.6%
7 4
 
1.3%
9 3
 
1.0%
Space Separator
ValueCountFrequency (%)
3592
100.0%
Other Punctuation
ValueCountFrequency (%)
. 102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3592
89.8%
0 162
 
4.0%
. 102
 
2.5%
1 36
 
0.9%
2 25
 
0.6%
4 21
 
0.5%
3 19
 
0.5%
5 18
 
0.4%
8 10
 
0.2%
6 8
 
0.2%
Other values (2) 7
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3592
89.8%
0 162
 
4.0%
. 102
 
2.5%
1 36
 
0.9%
2 25
 
0.6%
4 21
 
0.5%
3 19
 
0.5%
5 18
 
0.4%
8 10
 
0.2%
6 8
 
0.2%
Other values (2) 7
 
0.2%

S
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
S
521 
479 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd rowS
3rd rowS
4th row
5th row

Common Values

ValueCountFrequency (%)
S 521
52.1%
479
47.9%

Length

2023-07-19T17:24:41.880206image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:41.923542image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
s 521
100.0%

Most occurring characters

ValueCountFrequency (%)
S 521
52.1%
479
47.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 521
52.1%
Space Separator 479
47.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 521
100.0%
Space Separator
ValueCountFrequency (%)
479
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 521
52.1%
Common 479
47.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 521
100.0%
Common
ValueCountFrequency (%)
479
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 521
52.1%
479
47.9%

.13
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
926 
G
 
64
D
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters3
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th rowG

Common Values

ValueCountFrequency (%)
926
92.6%
G 64
 
6.4%
D 10
 
1.0%

Length

2023-07-19T17:24:42.071943image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:42.116741image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
g 64
86.5%
d 10
 
13.5%

Most occurring characters

ValueCountFrequency (%)
926
92.6%
G 64
 
6.4%
D 10
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Space Separator 926
92.6%
Uppercase Letter 74
 
7.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 64
86.5%
D 10
 
13.5%
Space Separator
ValueCountFrequency (%)
926
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 926
92.6%
Latin 74
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 64
86.5%
D 10
 
13.5%
Common
ValueCountFrequency (%)
926
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
926
92.6%
G 64
 
6.4%
D 10
 
1.0%

.14
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
954 
P
 
24
D
 
13
G
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters4
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
954
95.4%
P 24
 
2.4%
D 13
 
1.3%
G 9
 
0.9%

Length

2023-07-19T17:24:42.155367image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:42.200582image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
p 24
52.2%
d 13
28.3%
g 9
 
19.6%

Most occurring characters

ValueCountFrequency (%)
954
95.4%
P 24
 
2.4%
D 13
 
1.3%
G 9
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Space Separator 954
95.4%
Uppercase Letter 46
 
4.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 24
52.2%
D 13
28.3%
G 9
 
19.6%
Space Separator
ValueCountFrequency (%)
954
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 954
95.4%
Latin 46
 
4.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 24
52.2%
D 13
28.3%
G 9
 
19.6%
Common
ValueCountFrequency (%)
954
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
954
95.4%
P 24
 
2.4%
D 13
 
1.3%
G 9
 
0.9%

224700
Text

Distinct837
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:42.426870image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique836 ?
Unique (%)83.6%

Sample

1st row224690
2nd row224699
3rd row224707
4th row224705
5th row
ValueCountFrequency (%)
224690 1
 
0.1%
224890 1
 
0.1%
224732 1
 
0.1%
224707 1
 
0.1%
224705 1
 
0.1%
224709 1
 
0.1%
224708 1
 
0.1%
224717 1
 
0.1%
224720 1
 
0.1%
224715 1
 
0.1%
Other values (826) 826
98.8%
2023-07-19T17:24:42.731891image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2495
41.6%
2 984
 
16.4%
5 397
 
6.6%
4 388
 
6.5%
1 289
 
4.8%
7 271
 
4.5%
3 255
 
4.2%
6 243
 
4.0%
0 232
 
3.9%
8 224
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3505
58.4%
Space Separator 2495
41.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 984
28.1%
5 397
11.3%
4 388
 
11.1%
1 289
 
8.2%
7 271
 
7.7%
3 255
 
7.3%
6 243
 
6.9%
0 232
 
6.6%
8 224
 
6.4%
9 222
 
6.3%
Space Separator
ValueCountFrequency (%)
2495
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2495
41.6%
2 984
 
16.4%
5 397
 
6.6%
4 388
 
6.5%
1 289
 
4.8%
7 271
 
4.5%
3 255
 
4.2%
6 243
 
4.0%
0 232
 
3.9%
8 224
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2495
41.6%
2 984
 
16.4%
5 397
 
6.6%
4 388
 
6.5%
1 289
 
4.8%
7 271
 
4.5%
3 255
 
4.2%
6 243
 
4.0%
0 232
 
3.9%
8 224
 
3.7%
Distinct611
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:42.925617image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10000
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique610 ?
Unique (%)61.0%

Sample

1st rowB-20 6688
2nd rowB+38 5108
3rd row
4th row
5th row
ValueCountFrequency (%)
3 26
 
2.1%
7 18
 
1.5%
8 16
 
1.3%
2 16
 
1.3%
10 16
 
1.3%
b+51 14
 
1.1%
1 13
 
1.1%
11 13
 
1.1%
16 12
 
1.0%
13 12
 
1.0%
Other values (477) 1064
87.2%
2023-07-19T17:24:43.155540image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5728
57.3%
B 610
 
6.1%
1 469
 
4.7%
+ 459
 
4.6%
5 377
 
3.8%
2 364
 
3.6%
4 339
 
3.4%
0 336
 
3.4%
6 299
 
3.0%
3 290
 
2.9%
Other values (4) 729
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 5728
57.3%
Decimal Number 3052
30.5%
Uppercase Letter 610
 
6.1%
Math Symbol 459
 
4.6%
Dash Punctuation 151
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 469
15.4%
5 377
12.4%
2 364
11.9%
4 339
11.1%
0 336
11.0%
6 299
9.8%
3 290
9.5%
7 217
7.1%
9 181
 
5.9%
8 180
 
5.9%
Space Separator
ValueCountFrequency (%)
5728
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 610
100.0%
Math Symbol
ValueCountFrequency (%)
+ 459
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 151
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9390
93.9%
Latin 610
 
6.1%

Most frequent character per script

Common
ValueCountFrequency (%)
5728
61.0%
1 469
 
5.0%
+ 459
 
4.9%
5 377
 
4.0%
2 364
 
3.9%
4 339
 
3.6%
0 336
 
3.6%
6 299
 
3.2%
3 290
 
3.1%
7 217
 
2.3%
Other values (3) 512
 
5.5%
Latin
ValueCountFrequency (%)
B 610
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5728
57.3%
B 610
 
6.1%
1 469
 
4.7%
+ 459
 
4.6%
5 377
 
3.8%
2 364
 
3.6%
4 339
 
3.4%
0 336
 
3.4%
6 299
 
3.0%
3 290
 
2.9%
Other values (4) 729
 
7.3%

.1
Text

Distinct234
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:43.415016image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10000
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique233 ?
Unique (%)23.3%

Sample

1st row
2nd row
3rd row
4th rowC-41 15372
5th row
ValueCountFrequency (%)
c-41 13
 
2.8%
c-30 12
 
2.6%
c-29 11
 
2.4%
c-33 11
 
2.4%
c-44 10
 
2.1%
c-23 9
 
1.9%
c-42 9
 
1.9%
c-35 9
 
1.9%
c-31 9
 
1.9%
c-49 8
 
1.7%
Other values (184) 365
78.3%
2023-07-19T17:24:43.722543image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8261
82.6%
C 233
 
2.3%
- 233
 
2.3%
1 228
 
2.3%
3 191
 
1.9%
2 165
 
1.7%
4 153
 
1.5%
6 115
 
1.1%
5 112
 
1.1%
8 88
 
0.9%
Other values (3) 221
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 8261
82.6%
Decimal Number 1273
 
12.7%
Uppercase Letter 233
 
2.3%
Dash Punctuation 233
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 228
17.9%
3 191
15.0%
2 165
13.0%
4 153
12.0%
6 115
9.0%
5 112
8.8%
8 88
 
6.9%
7 81
 
6.4%
9 75
 
5.9%
0 65
 
5.1%
Space Separator
ValueCountFrequency (%)
8261
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 233
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 233
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9767
97.7%
Latin 233
 
2.3%

Most frequent character per script

Common
ValueCountFrequency (%)
8261
84.6%
- 233
 
2.4%
1 228
 
2.3%
3 191
 
2.0%
2 165
 
1.7%
4 153
 
1.6%
6 115
 
1.2%
5 112
 
1.1%
8 88
 
0.9%
7 81
 
0.8%
Other values (2) 140
 
1.4%
Latin
ValueCountFrequency (%)
C 233
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8261
82.6%
C 233
 
2.3%
- 233
 
2.3%
1 228
 
2.3%
3 191
 
1.9%
2 165
 
1.7%
4 153
 
1.5%
6 115
 
1.1%
5 112
 
1.1%
8 88
 
0.9%
Other values (3) 221
 
2.2%

.2
Text

Distinct348
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:43.970723image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10000
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)34.7%

Sample

1st row
2nd row
3rd rowP-52 12237
4th rowP-41 9991
5th row
ValueCountFrequency (%)
4 19
 
2.7%
5 15
 
2.2%
2 14
 
2.0%
1 14
 
2.0%
3 14
 
2.0%
p-41 13
 
1.9%
6 13
 
1.9%
p-30 12
 
1.7%
p-33 11
 
1.6%
10 11
 
1.6%
Other values (253) 558
80.4%
2023-07-19T17:24:44.261177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7644
76.4%
P 347
 
3.5%
- 347
 
3.5%
1 220
 
2.2%
3 209
 
2.1%
4 194
 
1.9%
2 177
 
1.8%
5 170
 
1.7%
6 160
 
1.6%
9 147
 
1.5%
Other values (3) 385
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Space Separator 7644
76.4%
Decimal Number 1662
 
16.6%
Uppercase Letter 347
 
3.5%
Dash Punctuation 347
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 220
13.2%
3 209
12.6%
4 194
11.7%
2 177
10.6%
5 170
10.2%
6 160
9.6%
9 147
8.8%
7 139
8.4%
0 129
7.8%
8 117
7.0%
Space Separator
ValueCountFrequency (%)
7644
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 347
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 347
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9653
96.5%
Latin 347
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
7644
79.2%
- 347
 
3.6%
1 220
 
2.3%
3 209
 
2.2%
4 194
 
2.0%
2 177
 
1.8%
5 170
 
1.8%
6 160
 
1.7%
9 147
 
1.5%
7 139
 
1.4%
Other values (2) 246
 
2.5%
Latin
ValueCountFrequency (%)
P 347
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7644
76.4%
P 347
 
3.5%
- 347
 
3.5%
1 220
 
2.2%
3 209
 
2.1%
4 194
 
1.9%
2 177
 
1.8%
5 170
 
1.7%
6 160
 
1.6%
9 147
 
1.5%
Other values (3) 385
 
3.9%

0.66
Real number (ℝ)

HIGH CORRELATION 

Distinct218
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.81031
Minimum-0.19
Maximum4.99
Zeros6
Zeros (%)0.6%
Negative26
Negative (%)2.6%
Memory size7.9 KiB
2023-07-19T17:24:44.341113image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-0.19
5-th percentile0.04
Q10.5
median0.73
Q31.04
95-th percentile1.7
Maximum4.99
Range5.18
Interquartile range (IQR)0.54

Descriptive statistics

Standard deviation0.55092188
Coefficient of variation (CV)0.67989027
Kurtosis9.2624961
Mean0.81031
Median Absolute Deviation (MAD)0.27
Skewness1.9677707
Sum810.31
Variance0.30351492
MonotonicityNot monotonic
2023-07-19T17:24:44.399499image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.02 21
 
2.1%
0.58 18
 
1.8%
0.98 18
 
1.8%
0.64 17
 
1.7%
0.55 16
 
1.6%
0.57 16
 
1.6%
1.04 14
 
1.4%
0.49 14
 
1.4%
0.95 14
 
1.4%
0.54 14
 
1.4%
Other values (208) 838
83.8%
ValueCountFrequency (%)
-0.19 1
 
0.1%
-0.14 1
 
0.1%
-0.12 1
 
0.1%
-0.11 2
0.2%
-0.1 3
0.3%
-0.07 3
0.3%
-0.06 1
 
0.1%
-0.05 2
0.2%
-0.04 3
0.3%
-0.03 3
0.3%
ValueCountFrequency (%)
4.99 1
0.1%
4.82 1
0.1%
3.92 1
0.1%
3.91 1
0.1%
3.51 1
0.1%
3.39 1
0.1%
2.96 1
0.1%
2.94 1
0.1%
2.87 1
0.1%
2.85 1
0.1%

F5
Text

Distinct237
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-07-19T17:24:44.632602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12000
Distinct characters45
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique143 ?
Unique (%)14.3%

Sample

1st rowK3V
2nd rowB9
3rd rowF0V
4th rowG8III
5th rowM0V:
ValueCountFrequency (%)
k0 80
 
8.1%
g5 68
 
6.9%
g0 40
 
4.1%
f5 37
 
3.8%
f8 33
 
3.4%
k0iii 32
 
3.3%
a0 32
 
3.3%
f0 26
 
2.6%
k2 24
 
2.4%
k1iii 22
 
2.2%
Other values (212) 588
59.9%
2023-07-19T17:24:44.932509image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8672
72.3%
I 627
 
5.2%
V 319
 
2.7%
K 286
 
2.4%
0 284
 
2.4%
F 271
 
2.3%
G 249
 
2.1%
5 209
 
1.7%
2 140
 
1.2%
A 115
 
1.0%
Other values (35) 828
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Space Separator 8672
72.3%
Uppercase Letter 2006
 
16.7%
Decimal Number 1027
 
8.6%
Other Punctuation 215
 
1.8%
Lowercase Letter 59
 
0.5%
Dash Punctuation 13
 
0.1%
Math Symbol 8
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 627
31.3%
V 319
15.9%
K 286
14.3%
F 271
13.5%
G 249
 
12.4%
A 115
 
5.7%
M 61
 
3.0%
B 57
 
2.8%
C 7
 
0.3%
N 6
 
0.3%
Other values (5) 8
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
p 18
30.5%
e 12
20.3%
m 6
 
10.2%
b 5
 
8.5%
n 4
 
6.8%
s 3
 
5.1%
v 2
 
3.4%
c 2
 
3.4%
a 2
 
3.4%
i 1
 
1.7%
Other values (4) 4
 
6.8%
Decimal Number
ValueCountFrequency (%)
0 284
27.7%
5 209
20.4%
2 140
13.6%
8 104
 
10.1%
3 103
 
10.0%
1 73
 
7.1%
9 34
 
3.3%
6 32
 
3.1%
7 28
 
2.7%
4 20
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 105
48.8%
/ 90
41.9%
: 20
 
9.3%
Space Separator
ValueCountFrequency (%)
8672
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Math Symbol
ValueCountFrequency (%)
+ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9935
82.8%
Latin 2065
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 627
30.4%
V 319
15.4%
K 286
13.8%
F 271
13.1%
G 249
 
12.1%
A 115
 
5.6%
M 61
 
3.0%
B 57
 
2.8%
p 18
 
0.9%
e 12
 
0.6%
Other values (19) 50
 
2.4%
Common
ValueCountFrequency (%)
8672
87.3%
0 284
 
2.9%
5 209
 
2.1%
2 140
 
1.4%
. 105
 
1.1%
8 104
 
1.0%
3 103
 
1.0%
/ 90
 
0.9%
1 73
 
0.7%
9 34
 
0.3%
Other values (6) 121
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8672
72.3%
I 627
 
5.2%
V 319
 
2.7%
K 286
 
2.4%
0 284
 
2.4%
F 271
 
2.3%
G 249
 
2.1%
5 209
 
1.7%
2 140
 
1.2%
A 115
 
1.0%
Other values (35) 828
 
6.9%

S
Categorical

Distinct9
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
S
500 
1
110 
X
104 
3
91 
4
83 
Other values (4)
112 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd rowS
3rd row2
4th row2
5th rowS

Common Values

ValueCountFrequency (%)
S 500
50.0%
1 110
 
11.0%
X 104
 
10.4%
3 91
 
9.1%
4 83
 
8.3%
2 71
 
7.1%
25
 
2.5%
G 13
 
1.3%
K 3
 
0.3%

Length

2023-07-19T17:24:45.008545image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-19T17:24:45.061365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
s 500
51.3%
1 110
 
11.3%
x 104
 
10.7%
3 91
 
9.3%
4 83
 
8.5%
2 71
 
7.3%
g 13
 
1.3%
k 3
 
0.3%

Most occurring characters

ValueCountFrequency (%)
1025
51.2%
S 500
25.0%
1 110
 
5.5%
X 104
 
5.2%
3 91
 
4.5%
4 83
 
4.2%
2 71
 
3.5%
G 13
 
0.7%
K 3
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 1025
51.2%
Uppercase Letter 620
31.0%
Decimal Number 355
 
17.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 500
80.6%
X 104
 
16.8%
G 13
 
2.1%
K 3
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 110
31.0%
3 91
25.6%
4 83
23.4%
2 71
20.0%
Space Separator
ValueCountFrequency (%)
1025
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1380
69.0%
Latin 620
31.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1025
74.3%
1 110
 
8.0%
3 91
 
6.6%
4 83
 
6.0%
2 71
 
5.1%
Latin
ValueCountFrequency (%)
S 500
80.6%
X 104
 
16.8%
G 13
 
2.1%
K 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1025
51.2%
S 500
25.0%
1 110
 
5.5%
X 104
 
5.2%
3 91
 
4.5%
4 83
 
4.2%
2 71
 
3.5%
G 13
 
0.7%
K 3
 
0.1%

Interactions

2023-07-19T17:24:22.068697image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:20.566955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:20.894991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.191883image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.486111image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.778440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:22.116584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:20.621908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:20.946632image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.239785image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.534623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.826485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:22.166400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:20.672761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:20.995677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.289160image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.583734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.875396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:22.213361image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:20.724308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.045712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.336688image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.629834image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.922138image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:22.263918image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:20.788991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.093711image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.386483image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.679876image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.972299image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:22.398794image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:20.845878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.142763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.436058image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:21.728595image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-19T17:24:22.019576image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-07-19T17:24:45.129043image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
19.1019.20430.00200.66.1H.1.20.3T0.03L.4.5.6.7.8.91.10.11.12.1S.13.14S
11.000-0.0321.000-0.0280.0120.0310.0130.0000.0000.0000.0390.0000.0000.0300.0460.0190.0400.0000.0000.0000.0380.0540.0850.0000.0440.0470.0220.0270.0100.0330.0530.0800.0510.073
9.10-0.0321.000-0.0320.9980.7620.0530.0000.1620.1840.1770.0000.0540.2690.2100.3670.0110.0790.2520.1680.1010.1160.0980.0980.0000.2120.0970.0470.0000.0000.0000.6940.5930.2020.246
11.000-0.0321.000-0.0280.0120.0310.0130.0000.0000.0000.0390.0000.0000.0300.0460.0190.0400.0000.0000.0000.0380.0540.0850.0000.0440.0470.0220.0270.0100.0330.0530.0800.0510.073
9.2043-0.0280.998-0.0281.0000.7570.0740.0000.1610.1860.1760.0290.0650.2770.2090.3690.0000.0830.2500.1710.1080.1020.1030.1060.0000.2130.1020.0310.0000.0000.0000.6970.6000.2000.235
0.00200.0120.7620.0120.7571.0000.2050.3430.4320.3440.3600.4070.3020.3830.5890.3600.0000.3950.6560.2080.3430.5420.0690.2930.7030.3880.5720.2350.0000.0000.0000.1050.3350.3940.289
0.660.0310.0530.0310.0740.2051.0000.0420.4390.1410.0290.0000.0110.1740.5110.4310.1000.0000.4200.2470.4420.4080.0360.0350.0310.1810.0000.1910.0000.0000.0000.1780.1950.2650.196
0.0130.0000.0130.0000.3430.0421.0000.0450.0940.9610.2030.6670.2410.2170.2360.9990.8630.0000.4400.0000.0000.5450.5840.6910.6410.7500.7150.6900.6730.6720.0740.0000.2690.128
.10.0000.1620.0000.1610.4320.4390.0451.0000.2030.0660.1980.0410.1030.4450.4180.0840.0460.5460.6650.7410.4840.0420.0000.0170.2360.0000.2090.0230.1300.1610.0960.2250.2610.357
H.10.0000.1840.0000.1860.3440.1410.0940.2031.0000.0960.0000.0870.4600.2580.4760.1400.0950.6980.1660.1400.1500.0940.0870.0930.1140.0000.1290.0950.0270.0000.0000.1650.0000.104
.20.0000.1770.0000.1760.3600.0290.9610.0660.0961.0000.2400.7370.2770.2240.2060.9220.7520.0000.3400.0630.0740.5290.6420.6650.6390.6880.4880.5980.4870.5450.0640.0000.2960.168
00.0390.0000.0390.0290.4070.0000.2030.1980.0000.2401.0000.3900.2130.2240.0940.3080.3490.1840.1800.1930.2090.3440.3560.7440.2220.2470.3070.1900.3910.3150.0820.1310.2800.146
.30.0000.0540.0000.0650.3020.0110.6670.0410.0870.7370.3901.0000.1520.2110.1480.9440.8010.0000.3980.0000.0000.4820.6400.6760.5600.6260.5900.5570.6650.6290.0830.0000.2180.147
T0.0000.2690.0000.2770.3830.1740.2410.1030.4600.2770.2130.1521.0000.7410.9730.1870.2400.3360.1810.1080.1250.1450.1740.2380.1610.2930.1910.1250.2670.3040.1150.1470.1680.398
0.030.0300.2100.0300.2090.5890.5110.2170.4450.2580.2240.2240.2110.7411.0000.4820.1910.1890.4350.2280.4270.5430.1790.1880.2140.3860.2340.2680.0000.3070.3490.3760.4180.3780.304
L0.0460.3670.0460.3690.3600.4310.2360.4180.4760.2060.0940.1480.9730.4821.0000.2080.2130.3140.2930.4750.4280.2250.2410.2320.2940.2300.2580.1640.2080.2370.3030.3970.4200.276
.40.0190.0110.0190.0000.0000.1000.9990.0840.1400.9220.3080.9440.1870.1910.2081.0000.9960.0550.6180.0000.0000.7680.8080.9770.9030.3560.9080.9770.9720.9700.0700.0000.1920.044
.50.0400.0790.0400.0830.3950.0000.8630.0460.0950.7520.3490.8010.2400.1890.2130.9961.0000.0000.3570.0000.0000.5020.7350.6930.4960.7480.5980.5650.5370.5120.0760.0000.3480.189
0.0000.2520.0000.2500.6560.4200.0000.5460.6980.0000.1840.0000.3360.4350.3140.0550.0001.0000.3640.6610.7390.0000.0000.0000.4530.0000.0870.0000.0000.0000.0400.4070.2740.342
.60.0000.1680.0000.1710.2080.2470.4400.6650.1660.3400.1800.3980.1810.2280.2930.6180.3570.3641.0000.9050.6030.3650.4540.4380.3580.1660.3550.3630.3120.2930.1070.1570.2540.186
.70.0000.1010.0000.1080.3430.4420.0000.7410.1400.0630.1930.0000.1080.4270.4750.0000.0000.6610.9051.0000.7680.0660.0200.0000.1990.0200.2400.0290.1660.2020.0520.1600.3320.278
.80.0380.1160.0380.1020.5420.4080.0000.4840.1500.0740.2090.0000.1250.5430.4280.0000.0000.7390.6030.7681.0000.0000.0000.0000.3600.0000.1510.0000.0140.0000.0760.2190.2400.327
.90.0540.0980.0540.1030.0690.0360.5450.0420.0940.5290.3440.4820.1450.1790.2250.7680.5020.0000.3650.0660.0001.0000.7210.5550.4730.2810.4860.5090.6440.7210.1210.0610.1700.038
0.0850.0980.0850.1060.2930.0350.5840.0000.0870.6420.3560.6400.1740.1880.2410.8080.7350.0000.4540.0200.0000.7211.0000.5970.5750.5300.5860.5830.5630.5710.1080.0250.2200.173
10.0000.0000.0000.0000.7030.0310.6910.0170.0930.6650.7440.6760.2380.2140.2320.9770.6930.0000.4380.0000.0000.5550.5971.0000.6520.2410.6600.7060.6800.6810.0650.0000.2780.134
.100.0440.2120.0440.2130.3880.1810.6410.2360.1140.6390.2220.5600.1610.3860.2940.9030.4960.4530.3580.1990.3600.4730.5750.6521.0000.2050.4470.5310.3650.3680.0700.1890.3500.108
.110.0470.0970.0470.1020.5720.0000.7500.0000.0000.6880.2470.6260.2930.2340.2300.3560.7480.0000.1660.0200.0000.2810.5300.2410.2051.0000.3240.2070.2600.3890.0520.0000.2820.175
.120.0220.0470.0220.0310.2350.1910.7150.2090.1290.4880.3070.5900.1910.2680.2580.9080.5980.0870.3550.2400.1510.4860.5860.6600.4470.3241.0000.5400.6710.6300.1220.1020.6170.117
.10.0270.0000.0270.0000.0000.0000.6900.0230.0950.5980.1900.5570.1250.0000.1640.9770.5650.0000.3630.0290.0000.5090.5830.7060.5310.2070.5401.0000.6410.7400.0630.0000.1230.072
0.0100.0000.0100.0000.0000.0000.6730.1300.0270.4870.3910.6650.2670.3070.2080.9720.5370.0000.3120.1660.0140.6440.5630.6800.3650.2600.6710.6411.0000.7290.1050.1660.3780.000
0.0330.0000.0330.0000.0000.0000.6720.1610.0000.5450.3150.6290.3040.3490.2370.9700.5120.0000.2930.2020.0000.7210.5710.6810.3680.3890.6300.7400.7291.0000.0920.0000.3720.062
S0.0530.6940.0530.6970.1050.1780.0740.0960.0000.0640.0820.0830.1150.3760.3030.0700.0760.0400.1070.0520.0760.1210.1080.0650.0700.0520.1220.0630.1050.0921.0000.2920.0750.214
.130.0800.5930.0800.6000.3350.1950.0000.2250.1650.0000.1310.0000.1470.4180.3970.0000.0000.4070.1570.1600.2190.0610.0250.0000.1890.0000.1020.0000.1660.0000.2921.0000.1550.293
.140.0510.2020.0510.2000.3940.2650.2690.2610.0000.2960.2800.2180.1680.3780.4200.1920.3480.2740.2540.3320.2400.1700.2200.2780.3500.2820.6170.1230.3780.3720.0750.1551.0000.210
S0.0730.2460.0730.2350.2890.1960.1280.3570.1040.1680.1460.1470.3980.3040.2760.0440.1890.3420.1860.2780.3270.0380.1730.1340.1080.1750.1170.0720.0000.0620.2140.2930.2101.000

Missing values

2023-07-19T17:24:22.553955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-19T17:24:22.736432image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

H100 00 00.22+01 05 20.49.10.1H.1000.00091185+01.08901332.23.54-5.20-1.881.320.741.391.360.810.32-0.07-0.11-0.240.09-0.010.10-0.01.10.010.3400.7419.6430.0209.1300.019.30.4820.025T0.550.03L.49.20430.00200.01787.59.179.24.6.7.8.91.10.11.12.1.1.1S.13.14224700B+00 5077.1.20.66F5S
0H200 00 00.91-19 29 55.89.27G000.00379737-19.49883745+21.90181.21-0.931.280.703.101.740.920.12-0.14-0.24-0.290.010.21-0.02-0.19-0.280.1421.45210.5190.0339.3780.0210.9990.002G1.040.00I9.40170.00170.0151209.379.44C1O224690B-20 66881.04K3V4
1H300 00 01.20+38 51 33.46.61G000.00500795+38.859286082.815.24-2.910.530.400.630.570.470.060.090.040.43-0.01-0.060.030.240.070.210-0.4536.5760.0046.6210.005-0.0190.004G0.000.00H6.60810.00070.0081276.606.62C00000+3852I11S224699B+38 51080.00B9S
2H400 00 02.01-51 53 36.88.06H000.00838170-51.893546127.7562.850.160.530.590.970.650.65-0.22-0.09-0.030.240.200.080.180.08-0.31-0.180-1.4648.4710.0078.0920.0070.3700.009T0.430.01L8.14980.00110.0152018.128.181S224707P-52 122370.43F0V2
3H500 00 02.39-40 35 28.48.55H000.00996534-40.591224402.872.539.070.640.611.110.670.740.100.240.060.26-0.100.20-0.16-0.30-0.190.060-1.2459.6930.0148.6560.0100.9020.013T0.900.01L8.70770.00180.0191618.688.741224705C-41 15372P-41 99910.95G8III2
4H600 00 04.35+03 56 47.412.31G000.01814144+03.9464889318.80226.29-12.844.032.184.996.153.200.35-0.010.03-0.11-0.020.47-0.020.030.310.3542.9561.3360.020G1.550.03I12.44880.00850.0918712.3012.601G1.55M0V:S
5H700 00 05.41+20 02 11.89.64G000.02254891+20.0366021617.74-208.12-200.791.010.791.301.130.820.320.08-0.02-0.040.120.060.110.000.160.4300.21710.5420.0399.6790.0300.7400.020G0.790.02H9.67950.00210.0171049.659.72C1B+19 51850.79G0S
6H800 00 06.55+25 53 11.39.053H000.02729160+25.886474455.1719.09-5.661.700.931.951.540.880.27-0.66-0.36-0.38-0.120.36-0.21-0.240.320.1800.98810.4330.0559.1510.0291.1020.051T3.920.39O8.55220.16711.460777.1511.25327.50P1B1SGP224709B+25 50544.82M6e-M8.5e TcG
7H900 00 08.48+36 35 09.48.59H000.03534189+36.585937774.81-6.308.420.860.550.991.020.650.030.16-0.010.000.07-0.020.080.040.100.133-1.2699.9620.0258.7110.0151.0670.023T1.030.02L8.75340.00180.0141078.738.78C1224708B+35 51491.00G5S
8H1000 00 08.70-50 52 01.58.59H000.03625309-50.8670736010.7642.2340.020.770.731.100.980.82-0.13-0.240.110.01-0.070.060.00-0.18-0.22-0.1300.82109.1400.0118.6300.0100.4890.011T0.560.01L8.69940.00200.0191568.668.751S224717C-51 13738P-51 120650.51F6V2
9H1100 00 08.95+46 56 24.07.34H000.03729695+46.940001544.2911.09-2.020.520.510.840.530.540.090.200.31-0.300.00-0.110.060.210.260.050-0.23117.4460.0057.3640.0050.0810.007T0.090.01L7.37770.00100.0121537.367.40C1S224720B+46 42310.07A2S
H100 00 00.22+01 05 20.49.10.1H.1000.00091185+01.08901332.23.54-5.20-1.881.320.741.391.360.810.32-0.07-0.11-0.240.09-0.010.10-0.01.10.010.3400.7419.6430.0209.1300.019.30.4820.025T0.550.03L.49.20430.00200.01787.59.179.24.6.7.8.91.10.11.12.1.1.1S.13.14224700B+00 5077.1.20.66F5S
990H99300 12 22.14-08 42 35.28.88H003.09223756-08.709771532.0149.01-1.201.080.881.301.400.870.40-0.26-0.19-0.08-0.150.28-0.16-0.390.210.3801.4199310.0850.0289.0060.0190.9340.026T0.930.02L9.03690.00230.017829.009.06C1S805B-09 230.89G5S
991H99400 12 25.28-61 36 20.79.00H003.10531311-61.605763225.4730.03-25.410.660.740.930.720.90-0.120.04-0.13-0.090.070.030.07-0.03-0.140.0410.409949.4790.0169.0540.0160.4150.018T0.480.02L9.09360.00190.0221269.069.131825P-62 130.31F3V1
992H995H00 12 26.38+45 57 34.68.242H003.10993546+45.95960688*3.99-3.21-8.150.600.551.020.630.60-0.020.210.23-0.190.06-0.180.160.390.13-0.1301.8699510.5400.0288.5440.010*1.5830.218G1.590.24R*8.35780.00300.030191*8.318.40U200124+4558H12CSAAB910.1230.0261.230.67794B+45 241.59K5S
993H99600 12 28.20+20 14 03.88.18H003.11749211+20.2343993719.39216.41-22.170.820.551.000.950.700.290.090.070.020.060.040.080.050.160.4600.649968.9690.0128.2400.0100.6690.013T0.730.01L8.32010.00150.0161168.308.351S804B+19 180.68G5S
994H99700 12 29.82-56 24 48.09.91H003.12424830-56.413325062.9013.90-7.130.951.221.531.011.41-0.110.04-0.04-0.200.160.150.160.13-0.16-0.0900.0599710.4780.0279.9280.0260.5210.028T0.590.03L10.02770.00280.0381479.9410.081839P-57 350.58F6V1
995H99800 12 29.95+32 12 14.18.88H003.12479109+32.203916741.76-8.65-1.430.900.551.010.980.610.050.090.170.36-0.18-0.17-0.130.240.220.0140.489988.9010.0118.8730.0140.0220.015G0.010.01L8.88870.00160.0161178.868.921803B+31 120.01A0S
996H99900 12 30.12+14 33 49.38.442H003.12549160+14.56369614+24.69321.76-71.311.570.981.201.671.34-0.200.32-0.29-0.21-0.240.11-0.30-0.330.050.570-0.869999.3780.0158.5380.0120.7390.015T0.790.01L8.57970.00370.0311228.528.63U21OPB+13 130.84K0S
997H100000 12 30.13-22 04 01.58.73G003.12556151-22.0670826815.32215.67-96.101.180.711.342.080.830.050.01-0.13-0.240.060.060.06-0.280.26-0.3000.0210009.6140.0208.8410.0160.7070.002G0.760.00H8.88280.00250.0171088.858.91C1812B-22 23C-22 30P-22 140.76K0V+...4
998H1001H00 12 30.94-32 19 15.09.12G003.12892949-32.32082372*4.61-11.7720.361.090.831.401.330.790.090.060.30-0.120.150.40-0.01-0.35-0.11-0.1531.0910019.6490.0189.1710.018*0.4710.015G0.540.02H*9.22990.00240.020108*9.189.2600125-3219I12CSAAB1860.1590.0211.350.46824C-33 42P-33 180.54F3V3
999H100200 12 31.96-52 20 00.29.23H003.13317674-52.333375745.621.42-52.440.660.811.230.921.05-0.26-0.10-0.090.18-0.060.21-0.05-0.07-0.11-0.370-0.33100210.5020.0249.3430.0150.9950.022T0.970.02L9.39120.00170.0232099.359.44C1838P-53 261.02K0III1